{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ML Practices.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOe+Jdpr0h1ijoYhGUC+i2P"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y3B8NzYeWrHG"
      },
      "source": [
        "#Important Notes/Steps during ML workflows."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z2hMBJ3OWIxP"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CEzaIYKpXVYT"
      },
      "source": [
        "1. Adding an extra dimension to array."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3g547TNiW3kd",
        "outputId": "8fb486dc-4556-42a6-d2fd-443d14eee15a"
      },
      "source": [
        "X = np.linspace(0,10)\n",
        "X.shape"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(50,)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H6HU0S7qXTnB"
      },
      "source": [
        "X = X[:,np.newaxis]"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-2akCtAAXeld",
        "outputId": "a1fd1cfd-7433-4494-e3ab-1451eaf6d571"
      },
      "source": [
        "X.shape"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(50, 1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mrPqMW5jXlaC"
      },
      "source": [
        "#This is important since the Feature Matrix must always be 2D."
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ewNZiKA47qjG"
      },
      "source": [
        "# Validation Curves in SK-Learn.\n",
        "\n",
        "> Important Learning : How to fit complex/high order polynomials in SK-Learn."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j7_ZM_wJXsn-"
      },
      "source": [
        "from sklearn.preprocessing import PolynomialFeatures\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.pipeline import make_pipeline"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q1Qsy97M8Grx"
      },
      "source": [
        "def PolyReg(degree=2, **kwargs):\n",
        "\n",
        "  P = make_pipeline(PolynomialFeatures(degree),\n",
        "                    LinearRegression(**kwargs))\n",
        "  \n",
        "  return P\n",
        "\n",
        "\n",
        "def datamaker(N=20):\n",
        "\n",
        "  X = np.random.rand(N,1)**2\n",
        "\n",
        "  #ravel is flattening.\n",
        "  y = 10 - 1/(X.ravel() + 0.1)\n",
        "\n",
        "  return X,y\n"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "StbA9nDQ9hQm"
      },
      "source": [
        "X_train , y_train = datamaker(100)"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MAXoORl0Diih"
      },
      "source": [
        "### Fitting Polynomials of Different Degrees."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aLfhVRnWA5PT"
      },
      "source": [
        "#Let's go with three models. \n",
        "#Model 1 = Degree 1\n",
        "\n",
        "m1 = PolyReg(1).fit(X_train, y_train)\n",
        "\n",
        "#Model 2 = Degree 3\n",
        "m3 = PolyReg(3).fit(X_train,y_train)\n",
        "\n",
        "#Model 3 = Degree 5\n",
        "m5 = PolyReg(5).fit(X_train,y_train)"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GHDoyI5vDhai"
      },
      "source": [
        "#Test Data. \n",
        "X_test = np.linspace(0,1,100).reshape(100,1)"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X7Vsy59oEDfN"
      },
      "source": [
        "#Predictions\n",
        "\n",
        "\n",
        "\n",
        "yp1 = m1.predict(X_test) \n",
        "yp3 = m3.predict(X_test)\n",
        "yp5 = m5.predict(X_test)"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 543
        },
        "id": "lJomIe94EFGN",
        "outputId": "4f18a0c1-95d4-4b27-82ee-d534f4d7709d"
      },
      "source": [
        "#Plotting\n",
        "plt.figure(figsize=(12,6))\n",
        "plt.style.use('seaborn')\n",
        "\n",
        "\n",
        "plt.grid()\n",
        "plt.scatter(X_train.ravel() , y_train, color='black')\n",
        "plt.plot(X_test.ravel() , yp1 , lw=2, label='degree = 1')\n",
        "plt.plot(X_test.ravel() , yp3 , lw=2, label='degree = 3')\n",
        "plt.plot(X_test.ravel() , yp5 , lw=2, label='degree = 5')\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "plt.title('Regression with Higher Power Polynomials')\n",
        "plt.legend()\n",
        "plt.grid()"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAA88AAAIOCAYAAACGSD9mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzde1yUVf4H8M/MADNchpvAIKAIKgiD4AV1FG+paWqmu25lrVuutuqa6Wqllq25rfc085Ka2f4009a0crtomlmayZCieQFRQVFAGC5yG25ze35/EBPDgKAiA/h5v14GPOfMc77PzKEX3znn+Y5IEAQBRERERERERFQnsa0DICIiIiIiImrumDwTERERERER1YPJMxEREREREVE9mDwTERERERER1YPJMxEREREREVE9mDwTERERERER1YPJMxEREREREVE9mDwTERERERER1YPJMxEREREREVE9mDwTETWiBQsWIDQ01OpfdHQ0pkyZgvj4eFuH+EAMGTIEc+bMsXUYtaovtg0bNiA0NPSuz/v5558jNDQUKSkptbYvWLAAMTExdf7cEPca2/2oGrP6P6VSiaFDh2LFihXQarVNGs/9auzriYuLQ2hoKI4fP/6AIm589zP3KioqHlBUREQtj52tAyAiam08PT3x5Zdfmn82mUxIS0vDli1b8Pzzz2P37t2IjIy0YYSNb9++fbC3t7d1GLWqGdv8+fMREBCAl156qUnjWLhwIfR6fZOOeT+OHj0KBwcHAEBpaSnOnj2LlStX4tdff8Unn3wCkUhk4wjvTmu7nrvR0uYeEVFzxeSZiKiRicVieHt7WxxTKBTYsGEDBg4ciJ07d+Ltt9+2UXQPhqenp61DqFPN2M6ePYuAgIAmj0Mulzf5mPfDy8sLUqnU/HNgYCCMRiNef/11nDlzBj179rRhdHevtV3P3Whpc4+IqLnitm0ioibi6OiIwMBAZGVlmY8JgoDt27dj7Nix6NatG/r164dFixahqKjI4rHvvfce+vfvj8jISDz33HNITU1FREQENmzYAOD3raQHDx7EmDFj0LdvX/Njjx8/jokTJ6J3797o0aMH/va3v1lsNdbpdFixYgWGDBmCrl27IiYmBvPnz0d+fr65z549ezBmzBh069YNvXr1wuTJk5GQkGBur7k1uri4GG+++Sb69++PiIgIDBo0CEuWLEFpaam5z1/+8hfMmDED3377LUaNGoXIyEg8/vjjOHbsWJ3P4cCBA7Fy5UqrY9WvFwDWr1+P/v37QxAEi9hCQ0Nx48YNbNy4EaGhoUhPTzc/Ji0tDc8//zyioqLQp08fbNy4sc447kXNrbPFxcWYN28eevbsiZ49e+K1117Dzz//jNDQUMTFxVk8tr7YcnJyMG/ePPNrOHr0aOzbt8+iT2hoKLZu3Ypp06aha9euuHz58l1fQ5cuXQAAt27dMh/74Ycf8NRTTyEyMhLdunXDM888g59//hkAzNdz9epVc/+qYzVfxyFDhmD16tXN+npq+vjjj9GlSxekpaVZHNdoNAgLC8Pu3buRnp6O0NBQHDhwAG+99RZUKhWio6MxY8YM5Obmmh8jCAK2bduGESNGICIiAr1798ZLL72EGzdumPts2LAB3bt3x/nz5zF+/HhERkZixIgR+Pnnn5GUlIQJEyYgKioKo0aNglqtNj+u5twrKSnBkiVLMGDAACiVSgwcOBCvv/66xe98TUlJSfjb3/4GlUqFyMhIjBo1Cjt37mzgM01E1DoweSYiaiI6nQ5paWnw8/MzH9u8eTNWrFiB0aNH48svv8SKFStw4sQJzJw509xnz549WL9+PcaPH4/9+/fjj3/8I+bMmVPrNswtW7Zg9uzZ+OKLLwAAv/zyC6ZNmwYfHx/s3r0bO3bsgE6nw8SJE3H79m0AwKZNm/DNN99g6dKlOHz4MNatW4fExES8+uqrAIDY2FgsXrwYf/3rX/HNN99g586dcHNzw+TJk1FWVlbrtU6fPh1Hjx7F4sWLcfDgQcyfPx9ffvkl5s2bZ9Hv6tWr+Pzzz7F69Wrs3bsXjo6OmDdvXp3njYmJwenTp80/X7t2DcXFxTAYDEhOTjYfj4uLQ//+/a224h49ehQAMHnyZJw4cQJt27Y1ty1ZsgQvvPAC9u/fj5EjR2LDhg2IjY2tNY7GsHjxYhw+fBiLFi3C3r174ePjg7feeqvWvneKTafT4fnnn0d8fDwWL16Mr776CmPHjsUbb7yB/fv3W5xn79696NmzJw4ePIigoKC7jrkqkat63k6ePIm///3v6NKlC/bt24c9e/ZAoVBg6tSpSEhIQHR0NGQyGU6dOmU+h1qtRtu2bS2OpaWlISMjAwMGDGjW11PT2LFjIZPJrOI6ePAgpFIpxowZYz62ceNG+Pv7Y8+ePVixYgWOHz+O9evXm9vXr1+Pd999F88++yy+/vprbNq0CTdu3MDzzz+PkpIScz+DwYC1a9di4cKF2Lt3L6RSKV5//XUsXboUc+fOxd69e2FnZ4eFCxfWed1LlizBV199hRUrVuDIkSNYs2YN4uLisGjRojofM336dLi4uGDnzp04cOAAJk2ahJUrV+LAgQP1PMtERK0Hk2cioiaQm5uLRYsWQavV4tlnnwUA6PV6fPjhhxg7diymTp2K9u3bm1eA4uLicObMGQDAF198AaVSiTlz5iA4OBjjxo3DH//4x1rH6devH4YNGwZfX18AwNatW+Hv74+3334bnTp1QteuXbFmzRpotVp8+umnAICEhASEhoaib9++aNu2LaKjo/HBBx+Yk+eLFy/C0dERTzzxBPz9/dGlSxcsXboUW7duhUQisYrh7NmzOH36NF577TUMGzYM7dq1w6hRozB9+nR89913yMzMNPfNysrCihUrEB4ejtDQUPz5z39GQUGBxWpbdTExMUhMTDSvYKvVakRFRUGpVJpXa8vKynDu3DkMGDDA6vFeXl4AACcnJ3h7e1vE/8wzz2DAgAEICgoy3w997ty5WuOobvz48ejevbvVv6+++qrOx5SVleHQoUN45plnMHbsWAQHB2POnDkICQmptf+dYjty5AhSUlKwdOlSDBw4EB06dMDUqVMxZMgQbN682eI8crkcU6dORUBAgPn+34YwGo349ddfsXbtWkRERKBHjx4AgA8//BAdO3bEv/71L4SEhCA0NBSrVq2Ci4sLdu/eDalUiujoaIs3PNRqNZ599lkkJiaai3Wp1Wo4OzujR48ezfp6apLL5Rg1ahS++OILCIJgPn7gwAGMGDHCYrt0p06dMGXKFAQGBmLYsGHo0aMHLly4AKDyDZAdO3bgT3/6E55//nl06NAB0dHRWLZsGTIzM3HkyBHzeXQ6HaZMmYIePXogNDQU48aNQ1ZWFp588kn07t0bISEhGDduHNLT0612sFSZM2cO9u3bh5iYGLRt2xa9evXCyJEjceLECYvrqJKXl4fMzEw8+uij6Ny5MwICAvDUU0/h008/Ra9evRr8vBMRtXRMnomIGlleXp5FEhUVFYWYmBhcuXIFmzZtQlRUFAAgJSUFWq3WqgquSqUCACQmJgKoXJXr2rWrRZ/BgwfXOnZERITFz+fPn4dKpbJIEr28vNC5c2fz+YcOHYqffvoJs2bNwoEDB5CXlwdfX19zleeYmBiYTCY8/fTT+OSTT3D9+nU4OTkhKiqq1oSlKiGIjo62ON69e3eL6wIq7zutfk+yh4cHANT5R3+/fv1gNBpx9uxZAJVJV3R0NKKjo80rmWfOnIHRaES/fv1qPUddunXrZv6+KqbqK3512bhxI/bv32/1b8iQIXU+5tatW9Dr9Q1+Xe8U27lz52Bvb4/evXtbPKZv375ITU21uIaa8+NOVCqVeQ5HRkZi4sSJCAsLw9atWyEWV/75cOHCBfTs2dNihd/BwQERERHm17n6bgGtVouEhAQ8/vjjaNu2rbn6vFqtRp8+fWBvb9/sr6emCRMmICMjw/zmTXp6Os6dO4cnn3zSol/V730VT09PFBYWAqjcQVFSUmL1OxMeHg6pVGo1tlKpNH/v5uYGAAgLC7M6VlxcXGvMYrEYO3fuxGOPPYbo6Gh0794d27dvR2lpKXQ6nVV/T09PdO/eHYsXL8Y777yDX375BXq9HuHh4Vb1HYiIWjMWDCMiamTu7u7Ys2eP+eeLFy9i7ty5mDJlCgYNGmQ+XrXq9sYbb+DNN9+0Ok9OTg4AoKCgAM7OzhZtdRXoqlkYSKvVYv/+/fjmm28sjldUVJgT3wkTJkChUGD37t147bXXoNPpoFKpsHDhQnTq1Anh4eHYs2cP/vOf/2D9+vVYvHgxOnXqhLlz52Lo0KFWMVRdV81YXFxcAFgmpE5OThZ9qpKW2la/qq47PDwcp06dQr9+/fDLL79g4sSJMJlM+O9//wugMhGLiIgwJ+IN5ejo2OA4qmvbti0CAwOtjtd8zaorKCiotU9dr+udYtNqtdDr9VYFrwwGA4DKeVQ1jqur6x2vpbq9e/eaq5RLJBJ4eXlBJpNZ9NFqtebXtTpnZ2fzfcD9+/fHypUrcfPmTSQnJ8PX1xd+fn7mNzwGDRqEuLg4zJgxo0VcT02RkZFQKpX4/PPPoVKpcODAAQQFBVklwnXN9apxAevfGbFYDCcnJ6s3caqfq+o8DZ2/giBgypQpyMzMxIIFCxAREQGpVIqdO3fWeQ+zSCTChx9+iI8++ggHDx7E+++/D7lcjieffBJz5sy5q1V/IqKWjMkzEVEjk0gkFslUYGAgDh06hKVLlyImJgbu7u4Afl8devXVVzFw4ECr81T9Ie3g4IDy8nKLtqrkqz6urq7o379/rR/LVP0P3kceeQSPPPIIdDodTp48iTVr1mDq1Kn4/vvvIRKJzAWeBEHAhQsX8MEHH+Cll17CgQMH0KFDB6sxgcpVr+p/0Fetgt1NwlOb/v374/Tp07h8+TJKS0vRrVs3mEwmFBQUICUlxXy/c3NW9dzXvLe7oa9rda6urrXed1ul+n3dd6Ndu3YW1alrI5fLa/2cZK1Wa56/ISEh8PHxwalTp3D58mX06dMHQOXOhL179yIlJQU5OTnmbfbN/Xpq8/TTT2PFihUoLy/HgQMHrFad61P9d6Y6k8mEkpKSRq2WfeXKFSQlJeFf//qXxe0fta04V+fs7Iy///3v+Pvf/47s7Gx89dVXWLduHWQyGWbPnt1o8RERNWfctk1E1ARef/11lJWVYfny5eZjQUFBcHV1RVpaGgIDA83/AgICYDAYzKuQgYGBOH/+vMX5Dh061KBxu3XrhpSUFIvzBwYGwmAwwNvbGyaTCYcPHzbfh+zg4IDBgwdj1qxZyMjIQGFhIeLj483314pEIkRGRmLJkiUwGo24cuWK1ZhVn2Fd/T5XAIiPj4dYLEZ4eHgDn7XaxcTE4Pz58zh27Jh567hMJkNERASOHTuGhISEWu93rq4hK8oPUvv27SESie75da2uW7duKC8vR1lZmcVrLJPJ4Orq+kBXBaOiohAfH2/xfFZUVODixYsWW9Krtm7Hxsaat2NHR0cjISEBx44dQ4cOHdCuXbsWcz01Pf744xCJRNi2bRuSk5Pxhz/84a7GDQoKglwutyiiBlTuWtHpdHcc+25VFRqsvstBq9Xi8OHDAGr/3dBoNBaFwXx8fDBlyhTExMTg0qVLjRYbEVFzx+SZiKgJ+Pr64qWXXsL+/fvNH3tjZ2eHF154AZ988gk++ugjpKam4tKlS3jttdfw5JNPQqPRAABGjhyJCxcuYNu2bbhx4wb+97//mf/Qrc8LL7yAy5cvY/HixUhKSkJqaiq2bt2KMWPG4NixYxCLxdi2bRv+8Y9/4PTp08jMzERCQgL++9//IiQkBO7u7vjhhx8wY8YMHD58GBkZGbh27Rq2bNkCmUxW6x/1kZGRUKlUWLFiBX788UekpaXhf//7H7Zs2YJx48bBx8fnvp7L7t27QyKR4JNPPjGvYgKVydjHH39svh+7NlWJ9q+//oqkpKQ6761+0Nzc3BATE4O9e/fiu+++Q2pqKtavX2/x0VkN9cgjjyAkJASvvPIKTp48iYyMDBw7dgwTJ07EP//5zwcQ/e9eeOEFXLt2DYsXL0ZKSgouXbqEOXPmoKKiAn/5y1/M/WJiYnDy5ElcvXrVnDwHBQXB3d0dH3/8scVOgZZwPTU5OzvjiSeewObNmzFkyJC7/txze3t7/PWvf8Vnn32GXbt2IS0tDbGxsViwYAGCg4MxbNiw+700s+DgYLi5uWHXrl24fv06fv31V7zwwgvmMeLi4qx2RBQVFeHll1/GmjVrkJycbC5idubMGat704mIWjNu2yYiaiLPPfccvvjiCyxatAhff/01HB0dMW3aNDg7O2PXrl1YtWoVHBwc0KtXL+zatQsKhQIAMGXKFOTk5GDr1q3YtGkTevfujWXLlmHkyJH1bkONjo7Gtm3bsGHDBjz99NMwmUwIDQ3F2rVrzfcrv/fee1i5ciVmz56NwsJCeHh4oHfv3vjXv/4FAJg9ezYkEglWrlyJ7OxsODk5ISwsDB988EGdW2jfe+89rFq1CgsXLkRBQQEUCgUmTpxo8RFc98rBwQF9+vTBDz/8YPGHe1WV8BEjRtRaBRyoXDmfMWMGtmzZgj//+c/Ytm3bfcdzr5YvX45FixbhlVdegZOTE0aPHo3Zs2dj5syZ9b6u1Tk4OGD79u1YvXo1Xn75ZRQWFsLLywujR4/GrFmzHuAVAL1798bmzZuxceNG/OEPf4BEIkFUVBQ++ugjdOzY0dwvJiYGr776Kvz8/ODv728+3rNnTxw6dMhip0BLuJ7ajBo1Cp988gmeeuqpexp7xowZkEql2LFjB5YtWwa5XI4BAwbg1VdfbdTVdicnJ6xevRrLly/H2LFjERgYiH/84x/o3r07zp49i1mzZmHTpk0Wj+ncuTO2bNmCzZs3Y9euXTAajfD398fkyZMxadKkRouNiKi5Ewm23rtGRER3ZDQacfv2bYuqtpcuXcK4cePw7rvvYuTIkTaMju6VTqeDVqu1WKXcvn07li9fjtjY2LtevSTbWrJkCeLi4u74EWVERNSycds2EVEz9/nnn6N///7YsWMH0tPTcf78ebz11lvw9fWttdAYtQyvv/46Ro0ahaNHjyIjIwM//vgjtm3bhqFDhzJxbiEMBgMyMzPx0UcfYdeuXZg/f76tQyIiogeIK89ERC3A9u3b8emnnyIjIwNyuRyRkZF45ZVXEBwcbOvQ6B6VlJTgnXfewZEjR3D79m34+Phg8ODBmD179n1XJKemkZmZiaFDh8LX1xcvvvgixo8fb+uQiIjoAWLyTERERERERFQPbtsmIiIiIiIiqgeTZyIiIiIiIqJ6MHkmIiIiIiIiqgeTZyIiIiIiIqJ62Nk6gOpycoptHUK9xGIRPD2dcft2CUwm1lqj5odzlFoCzlNq7jhHqbnjHKXmriXNUW9veYP6ceX5LonFIohEIojFIluHQlQrzlFqCThPqbnjHKXmjnOUmrvWOEeZPBMRERERERHVg8kzERERERERUT2YPBMRERERERHVg8kzERERERERUT2YPBMRERERERHVg8kzERERERERUT2YPBMRERERERHVg8kzERERERERUT2YPBMRERERERHVg8kzERERERERUT2YPBMRERERERHVg8lzE9q/fx/+9Kcxtg6DiIiIiIiI7hKTZ2o06elpmDLlL3jiiRG2DoWIiIiIiKhRMXmmRhEffwozZ05F27ZtbR0KERERERFRo7OzdQCtWULCRaxatRQZGWmIiIhEVFR3i/b4+FPYunUTrl1LgbOzM8aNG49Jk14AABiNRqxbtxoHD34NudwVM2bMwrZtW/Dcc5MxatQYzJw5FeHhEYiLOwkfHwXefnsdsrIysXbtKly8eB5GowkxMQMwd+48ODu71DteTUOG9Kv1eFRUd6xd+57V8cLCQrz77iYkJl7E+fPn7udpIyIiIiIianaYPD8gRqMR//znfAwbNhxTpmxHcvJVvPHGPEgkEgBAdrYGCxa8jLlz52H48JFITb2Ol19+CX5+ARg+/DHs2/dfHD16BO+/vx3e3j5Yvvwt5ObmWIxx5MghLFmyEmFhSgiCgAULXkbXrlH47LPlKCsrxeLFC7Fx4zrMn7+w3vFqOnr05F1d75AhwwAAiYkX7/EZIyIiIiIiar5adPJ8Kikb+3+6hnKdsUnGkzlIMH5wR4zoF1xv36SkS8jNzcFzz02BVCqFUhmBgQMH4+effwJQmfgGBQVj5MjHAQAdO3bCuHHjcejQAQwf/hhiY3/Go48+huDgjgCA6dNn4vjxHyzGCA+PQHh4BADg0qUEXL+egs2bP4RMJoNMJsPkyVMxd+5MzJv3er3jERERERERUd1adPL8bdwNZOaVNumYB2JvNCh5zsnRQC6Xw8XFxXysXbv25u8zMtKRlJRosT1aEAS0bx8IAMjLy0W/fv3Nbe3bB8LZ2dliDF/f3+8vzshIh9FoxOjRQy36GI1GFBQU1DseERERERFRYzGZBFuH0OhadPI8sk8gvmjiledRfRuWbOp0ehiNlnFVn0BSqRQqVQxWrVpb6+MFQYBEYvnyiESW9d2qtoBXnc/R0QnffXe81vPVN15Nd3vPMxERERERPdzKKgyIv5wDdWIWLt3IR0d/Nyz4cw+IRSJbh9YoWnTyHN3FB9FdfJp0TDu7hhUo9/LyQklJCbRarXn1OTX1mrnd3z8Ax4//CEEQIPptMuXl5UIud4WDgwPc3T2g0WSa+6enp0GrLa5zPH//AJSVleLWrQz4+fkDAEpLS6DX6+Hm5l7veDXd7T3PRERERET08DEYTbhwLQ+xCRqcS86F3mAytyWnF6KswgBnmb0NI2w8/KiqB0SpjIBc7opdu3ZAp9Ph3LlfcfLkCXP7sGEjUFRUhB07PkRFRTkyMtIxZ86L2Lv3EwBAz569cPjwt7h58wa0Wi22bt0ER0fHOscLDu6Erl0jsW7dahQUFKC4uBirVi3Dv/+9qEHjERERERERNYRJEHAlrQAffZuEORtOYMNnF3A6KdsicfZxd8Tsp7vDzUVqw0gbV4teeW7OpFIZli9fjdWrl+PTT3cjIiIKEyb8Gfv27QEAuLm5Y8WKNdi48V189NF/4O7ugREjRmHChIkAgGef/QtSU69h0qRn4eOjwKxZc3H2bLx51bg2b765FO+8sxJPPjkGDg4O6NmzNxYuXNyg8e7XnDkv4ty5szAajTAajeZt3++8sxHduvVolDGIiIiIiMh20nO0UCdoEJeoQV5RuVW7i6M9eof5QKX0RWh7d3h6uiA/v8QGkT4YIkEQms2d3Dk5dW9Lbi7s7MTw8HBGfn4JDNXeWXkQdDqdeUu1wWDA0KExWLNmA6Kjez/Qcalla8o5SnSvOE+pueMcpeaOc5Sayu2icsQlahCboEF6jtaq3cFejB6dvaFSKhDewRN2ksrNzS1pjnp7yxvUjyvPzdS3336DTZvWY+PGrfDz88fOnf8HuVyOsLBwW4dGREREREStWEm5HqeTsqFO0OBKWgFqrraKRSKEB3mgr9IX3Tt7QebwcKSVD8dVtkDDh49Eaup1zJo1HSUlJejQIQjLlq2Gs7NL/Q8mIiIiIiK6C3qDEeeS86BO1OB8Si4MRusNysF+rlCFK9A7TAFXZ+uiw60dk+dmSiwWY/r0mZg+faatQyEiIiIiolbIZBJw+WY+YhM1iL+cg7IKg1UfhacT+oYr0EepgMLDyQZRNh9MnomIiIiIiB4SgiDgpkYLdWIWfrmUjfziCqs+rs4O6B3mg75KX3Twld+xaPHDhMkzERERERFRK5dbUAZ1ogbqRA1u5VpXwJY6SNAzpLLwV1igByRifqpxTUyeiYiIiIiIWiFtmR6nLmkQm6hBcnqhVbtELELX4DZQKRWI6uQFqb3EBlG2HEyeiYiIiIiIWokKvRG/Xs2FOiELF6/fhtFkXfirU4Ab+ip90auLD1wc7W0QZcvE5JmIiIiIiKgFM5pMuHQjH+oEDeKv5KBCZ7Tq4+flDFW4AqpwBbzcHW0QZcvH5JmIiIiIiKiFEQQBqVnFiE2oLPxVVKKz6uMhl6JPmAIqpQLtfFxY+Os+MXluQvv378PHH+/Avn1f2ToUIiIiIiJqgTT5pVAnVBb+0twutWp3lNohOtQbKqUvQtu5QyxmwtxYmDxToygqKsS6dWsQF3cSBoMBHTt2xosvzkZ4eIStQyMiIiIiatGKSnT45VJlwnztVpFVu51EhKiOXlApFYjs2Ab2diz89SAweaZGsXz5WxAEAbt27YNM5oitW9/DvHlzsH//QdjZcZoREREREd2Ncp0BZ6/kIjYxC4nX82ESLAt/iQCEtneHSumLnqHecJax8NeDxqzmAUpIuIhVq5YiIyMNERGRiIrqbtEeH38KW7duwrVrKXB2dsa4ceMxadILAACj0Yh161bj4MGvIZe7YsaMWdi2bQuee24yRo0ag5kzpyI8PAJxcSfh46PA22+vQ1ZWJtauXYWLF8/DaDQhJmYA5s6dB2dnl3rHq2nIkH61Ho+K6o61a9+zOv7II8MQGdkdbm7uAICRI8dgz57dyM+/DW9vn3t+DomIiIiIHhYGowkJ129DnajB2as50OlNVn3a+bhApVSgT5gCnq4yG0T58GLy/IAYjUb885/zMWzYcEyZsh3JyVfxxhvzIJFUbqHIztZgwYKXMXfuPAwfPhKpqdfx8ssvwc8vAMOHP4Z9+/6Lo0eP4P33t8Pb2wfLl7+F3NwcizGOHDmEJUtWIixMCUEQsGDBy+jaNQqffbYcZWWlWLx4ITZuXIf58xfWO15NR4+evKvrHT58pPn7/Px87NmzC1FR3eHl5X0Pzx4RERER0cNBEASk3CqC+rfCX9oyvVWfNq4yqJSVlbL9vV1sECUBLTx5PpN9Hl9fO4wKY0WTjCeVSDG20wgM86h9Vba6pKRLyM3NwXPPTYFUKoVSGYGBAwfj559/AlCZ+AYFBWPkyMcBAB07dsK4ceNx6NABDB/+GGJjf8ajjz6G4OCOAIDp02fi+PEfLMYID48w31N86VICrl9PwebNH0Imk0Emk2Hy5KmYO3cm5s17vXRsWhsAACAASURBVN7xGsszz/wRaWk30a1bD7z11nJW9CMiIiIiqkVmXgliEzSIS8xCTkG5VbuzzA69uvhApfRFpwA3iPl3tc216OT5yI1j0JRmN+mYh1N/xLCw+pPnnBwN5HI5XFx+f2eoXbv25u8zMtKRlJRosT1aEAS0bx8IAMjLy0W/fv3Nbe3bB8LZ2dliDF/fthbnMxqNGD16qEUfo9GIgoKCesdrLJ988jny8/Px0Uf/wYsv/g3bt38CmYzbSYiIiIiI8osrKgt/JWhwQ1Ns1W5vJ0a3TpWFv7oGt4GdRGyDKKkuLTp5HhY4qMlXnod3GNygvjqdHkaj5YeTm0y/3+QvlUqhUsVg1aq1tT5eEARIJJYvj0hk+ctTtQW86nyOjk747rvjtcdez3g13e09z9V5eHjgxRdn4+uv9yM29gQeeWRYg8YkIiIiImptSssNiL+SDXWCBkk38iHUaBeJgPBAD6iUvugR4g1HaYtO0Vq1Fv3K9PCJRA+fyCYd086uYe/+eHl5oaSkBFqt1rz6nJp6zdzu7x+A48d/hCAI5q3NeXm5kMtd4eDgAHd3D2g0meb+6elp0Gqt352qfr6yslLcupUBPz9/AEBpaQn0ej3c3NzrHa+mu7nnubS0BM8//wyWLl2FkJAuAACxWAxBEFhpm4iIiIgeOnqDCReu5UGdkIVfk/NgMFoX/gr0laOv0he9w3zg7iK1QZR0t7gP4AFRKiMgl7ti164d0Ol0OHfuV5w8ecLcPmzYCBQVFWHHjg9RUVGOjIx0zJnzIvbu/QQA0LNnLxw+/C1u3rwBrVaLrVs3wdHRsc7xgoM7oWvXSKxbtxoFBQUoLi7GqlXL8O9/L2rQePfDyckZ7dt3wHvvrUdubi4qKirw4Yfvw97eAV27drvv8xMRERERNXcmQcDlm/nY8W0S5m48gY2fX8DpyzkWibO3uwxj+nXA0r/1wZuTemF4r3ZMnFsQLgs+IFKpDMuXr8bq1cvx6ae7ERERhQkT/ox9+/YAANzc3LFixRps3PguPvroP3B398CIEaMwYcJEAMCzz/4FqanXMGnSs/DxUWDWrLk4ezb+jgW43nxzKd55ZyWefHIMHBwc0LNnbyxcuLhB492vRYvewvr172DixD9BEAR06hSCt99eB3d390Y5PxERERFRc5SerUVsYhZ+SdQgr8j6dlK5kz16d1FApVQg2M+VBXVbMJEgCDW33dtMTk7d25KbCzs7MTw8nJGfXwKDwXr7RWPS6XTmLdUGgwFDh8ZgzZoNiI7u/UDHpZatKeco0b3iPKXmjnOUmjvOUdu6XVQOdaIG6oQspOeUWLU72IvRI8QbqnBfhHfweCgLf7WkOertLW9QP648N1PffvsNNm1aj40bt8LPzx87d/4f5HI5wsLCbR0aEREREdFDp6Rcj9NJlYW/LqcVWLWLRSIogzzRV6lA987ekDpIajkLtWRMnpup4cNHIjX1OmbNmo6SkhJ06BCEZctWw9mZH4pORERERNQU9AYjziXnITYhCxeu5cFgtN6029HPFSqlL3qF+cDVyboQL7UeTJ6bKbFYjOnTZ2L69Jm2DoWIiIiI6KFhMglIupkPdYIG8VeyUVZhtOrj6+kElVIBVbgCPh5ONoiSbIHJMxERERERPdQEQcBNjRbqxCzEJWpQoNVZ9XFzdkCf8MrCX4EKOQt/PYSYPBMRERER0UMpp6DMXPgrM6/Uql3mIEHPEG+olL4IC/SAWMyE+WHG5JmIiIiIiB4axaU6nPqt8FdyRqFVu0QsQtfgNlApFejWyQsO9iz8RZWYPBMRERERUatWoTfi7NUcqBM0SLh+G0aTdeGvkAA3qJS+iO7iAxdHextESc0dk2ciIiIiImp1jCYTLqXmIzZBgzNXclChty785e/lDJVSgT7hCni5OdogSmpJmDwTEREREVGrIAgCrmcWQ52QhV8uaVBUqrfq4yGXVhb+ClegnY8LC39RgzF5bkL79+/Dxx/vwL59X9k6FCIiIiKiVkNzuxSxCVlQJ2qQnV9m1e4otUOvLt5QhfsipL07xEyY6R4weaZGMXPmVFy4cA4Sye8FFdq1C8SOHZ/YMCoiIiIiaq0KS3T45VJlpezrmcVW7XYSMaI6tYEq3BeRHdvA3k5sgyipNWHyTI1m/vw3MGrUGFuHQUREREStVFmFwVz4KzE1HybBsvCXCEBoe/fKwl+h3nCSsfAXNR4mzw9QQsJFrFq1FBkZaYiIiERUVHeL9vj4U9i6dROuXUuBs7Mzxo0bj0mTXgAAGI1GrFu3GgcPfg253BUzZszCtm1b8NxzkzFq1BjMnDkV4eERiIs7CR8fBd5+ex2ysjKxdu0qXLx4HkajCTExAzB37jw4O7vUO15NQ4b0q/V4VFR3rF37XiM+S0REREREdTMYTbh4/TbUCVn49WoudAaTVZ/2Pi5QKX3RO8wHnq4yG0RJDwMmzw+I0WjEP/85H8OGDceUKduRnHwVb7wxz7ytOTtbgwULXsbcufMwfPhIpKZex8svvwQ/vwAMH/4Y9u37L44ePYL3398Ob28fLF/+FnJzcyzGOHLkEJYsWYmwMCUEQcCCBS+ja9cofPbZcpSVlWLx4oXYuHEd5s9fWO94NR09evKur/n777/D7t0fQaPRIDw8AvPmvQ5//4B7ewKJiIiI6KElCAKSMwqhTtDgVFI2tGXWhb+83GTmwl/+3i42iJIeNi06eS4+/Qvy9n8BU0V5k4wnlsrgM348PIY/Um/fpKRLyM3NwXPPTYFUKoVSGYGBAwfj559/AlCZ+AYFBWPkyMcBAB07dsK4ceNx6NABDB/+GGJjf8ajjz6G4OCOAIDp02fi+PEfLMYID49AeHgEAODSpQRcv56CzZs/hEwmg0wmw+TJUzF37kzMm/d6vePdrw4dguHo6Ig33/w3TCYBa9euwssvv4SdOz+FvT23yxARERFR/W7llkCdmAV1gga5hdZ/4zvL7NArTIG+SgU6+buxUjY1qRadPN/+9iB0WZlNOmbuwQMIbEDynJOjgVwuh4vL7++CtWvX3vx9RkY6kpISLbZHC4KA9u0DAQB5ebno16+/ua19+0A4OztbjOHr29bifEajEaNHD7XoYzQaUVBQUO949+uVVxZY/Dx//kKMHDkE586dRXR070YZg4iIiIhan/ziCsQlaqBOzMJNjdaq3cFOjG6dvaAK90VEsCfsJCz8RbbRopNnz8dGIW//50268uw1clSD+up0ehiNlh/EbjL9XtBAKpVCpYrBqlVra328IAiQSCxfHpHI8n8U1StbS6VSODo64bvvjtd6vvrGq+l+73l2cnKGq6ub1VZzIiIiIqLScgPiL2dDnahB0o18CDXaRSIgvIMnVOEK9AjxhqO0Ract1Erc9Sz86aefMH/+fPTp0wdr11omYgcOHMDmzZuRnp6OoKAgzJ07F/3796/jTPdPHt0L8uheD+z8tbFrYIl7Ly8vlJSUQKvVmlefU1Ovmdv9/QNw/PiPEATBvN0kLy8XcrkrHBwc4O7uAY3m91X19PQ0aLXWJfirn6+srBS3bmXAz88fAFBaWgK9Xg83N/d6x6vpbu55LinRYvPmjZg0aQq8vLwBAAUFBSgoyDfHQkREREQPN73BhPMpeVAnZuFcch4MRuvCX0Ft5VCFVxb+cnOR2iBKorrd1Z6HDz74AEuWLEFgoPVW30uXLmH+/Pl45ZVXoFarMWnSJMycORNZWVmNFmxLolRGQC53xa5dO6DT6XDu3K84efKEuX3YsBEoKirCjh0foqKiHBkZ6Zgz50Xs3Vv5ucg9e/bC4cPf4ubNG9Bqtdi6dRMcHR3rHC84uBO6do3EunWrUVBQgOLiYqxatQz//veiBo13P5ydXZCYeAFr165CUVEhioqKsGbNCnTs2BkREZH3fX4iIiIiaplMgoDLN/Ox/WAS5mw4gfe+uID4yzkWibOPuyOeiOmAZVNV+OfzvfBor3ZMnKlZuqvkWSqVYt++fbUmz3v37sWgQYMwaNAgSKVSPPHEEwgJCcGXX37ZaMG2JFKpDMuXr8aJE8cwcuQj+M9/tmLChD+b293c3LFixRocP/4jRo4cgpdemoaYmIGYMGEiAODZZ/+CqKhumDTpWbzwwnN47LHRkMkc71gU4c03l0IQBDz55BhMmDAOJpMJCxcubtB492vZsjUQBOCZZ/6I8eNHw2DQ4+2334VYzHtSiIiIiB42adla7P0hGfM2n8TK3Wdx/NwtlFYYzO1yJ3sM7RmAhc/1xPJpKowbEAxfTycbRkxUP5EgCDVvMajXggULUFFRYbFt++mnn8agQYMwY8YM87HFixcjLy8PGzZsaNB5c3Lq3pbcXNjZieHh4Yz8/BIYavmMucak0+nMW6oNBgOGDo3BmjUbWICL7qgp5yjRveI8peaOc5Sau+Y4R/MKyysrZSdqkJFTYtUutZegR4gXVEpfhHfwgISLLK1ac5yjdfH2ljeoX6PdeV9QUAA3NzeLY25ubkhOTm7wOcRiEcTi5l1uXvJbdT/JA67yd/Dg19iwYR22bNkGPz8/7Nq1HXK5HF27RjT4vmt6ODXVHCW6H5yn1NxxjlJz11zmqLZMj1OXNDh5IQuX0wqs2sUiEbp2bIN+Eb7oEeINqYOklrNQa9Rc5mhjatSydfewiG3B09O5xXxWm6tr3fcfN4YJE55EZmY6Zs6cBq1Wi06dOmHTpk0ICFA80HGp9XjQc5SoMXCeUnPHOUrNnS3maIXeiFOJWfgxPh3xSRoYjNY5QJdADwzuEYD+3fx5//JDrjX9f7TRkmcPDw8UFFi+21RQUABPT88Gn+P27ZIWsfLs6uqIoqIyGGupENiYJk+ejsmTp1scy8+33gJDVF1TzlGie8V5Ss0d5yg1d009R00mAYmptxF7MQunkrJRrjNa9Wnbxgn9InzRN8IXPh6V9y+b9Abk5xus+lLr15L+P+rh4dygfo2WPEdERODixYsWxy5cuIDRo0c3+Bwmk2DxWcjNmdFoavZ79+nhxjlKLQHnKTV3nKPU3D3IOSoIAm5qtIhNyELcJQ0KtTqrPm4uDugTpkBfpS/aK1zMu0j5e0NVWtP/RxsteX7qqafwpz/9CT/++CP69u2Lr776CqmpqXjiiScaawgiIiIiInrAsgvKEJdQWfgrM6/Uql3mIEHPUG+olL4Ia+/R7HeOEjWWu0qeu3btCqCy8jMAHDlyBEDlCnNISAhWr16N5cuXIyMjA506dcL7778Pb2/vRg6ZiIiIiIgaU1GpDqcuZUOdmIWUjCKrdolYhMiObaBS+iKqYxs42LPwFz187ip5vnDhwh3bhw8fjuHDh99XQERERERE9OBV6Iw4ezUH6kQNEq7fhrGW2ydD2rlDpVQgOtQHLo72NoiSqPlo1GrbRERERETUfBlNJiSm5kOdkIUzV3JRobcu/BXg7QyV0hd9whRo4yazQZTU0iUXXMfJzDgEe7XDIN/+tg6n0TB5JiIiIiJqxQRBwLXMIqgTNDh1SYOiUr1VHw+5FKpwBVRKX7TzcbFBlNQa5Jbdxv7kb3A2p3LHclzmGUR5REJuJ7dxZI2DyTMRERERUSuUdbsU6t8Kf2Xnl1m1O0ntEN3FB32VCnRu5w6xiIW/6N6UGcpxKPUofkj7CQbh990MXRVd4OrgAqF1FNtm8kxERERE1FoUaivwy2+Fv65nFlu120nE6NapsvBX1+A2sLcT2yBKai1MggmxmafwVcohFOu15uNyexeM7fwYHlc+gsLCMhhMrSN7ZvJMRERERNSClVUYcOZKZeGvxNTbEGrU/RIB6BLoAZVSgZ4hPnCSMQWg+3clPxn7rn6FDG2m+ZidSIJH2g3AiA5DIJc5QSxuXW/O8DeHiIiIiKiFMRhN+CUhC4fVqTh7JQc6g/XKXnuFC1ThvugTroCHXGqDKKk1uqXNwpfXvsWF3ESL4929u2Jcp1Hwcmxjo8gePCbPREREREQtgEkQkJxeCHWiBqeSslFSZl34y8tNBpVSgT7hvvD3crZBlNRa3S7PxzfXvkNcVjwE/L69oZ2LH8Z3fgKdPYJtGF3TYPJMRERERNSMZeRooU7UQJ2gQV5RuVW7i6M9eoX5oG+4Lzr6u0LEwl/UiLT6EhxKPYrjGbEwmAzm424OrhjT8TH08e0Bsah1bc+uC5NnIiIiIqJmJr+4AnGJGqgTsnAzW2vV7mAnhiqiLXqGeiGsvQfsJA9H8kJNp8Koww9pP+G7G8dQbvz9TRtHO0cMDxyMwQExcJA42DDCpsfkmYiIiIioGSgt1+P05RyoE7Jw+WYBatT9gkgEKDt4QqVUoFeYAn6+bsjPL4Ghlvudie6VwWTAyVuncDD1CIp0v1dstxfbYXBAfwwPHAwneycbRmg7TJ6JiIiIiGxEbzDhfEoe1IlZOJecB4PROhEOausKlVKB3mEKuDlXrvTZ8SOmqJEZTAbEZcbj2xtHcbs833xcLBKjb9tojOwwDB4ydxtGaHtMnomIiIiImpBJEHDlZgHUiVk4nZSD0gqDVR8fD0eowhXoq/SFwvPhXOWjpmE0GaHOOo1DqUeRVy1pBoBu3l0xJngEfJ19bBRd88LkmYiIiIioCaRnaxGbkIW4SxrcLqqwand1skfvMAVUSl8EtZWz8Bc9UEaTEXFZ8fg29XurpDm8TShGBz2KDq7tbRRd88TkmYiIiIjoAckrLIc6MQvqRA0yckqs2qX2EvQI8UZfpQJhHTwgEXM7Nj1Y9SXNozo8iiA3Js21YfJMRERERNSItGV6nL6cDfXFLFxJL7Rql4hFUAZVFv7q3skbUgeJDaKkh43OqENs5ml8f/OYddLsGYpRQcMQ5BZoo+haBibPRERERET3Sac34lxKHtQJWTifkgejqWatbKCTv1tlpewuPpA7PVwf8UO2U6ovxfGMWPyQdgJaveXuhzDPEIwOepRJcwMxeSYiIiIiugcmk4BLN/OhTsjCmSs5KKswWvVp28YJKqUvVOEKeLs72iBKelgVVBTiaNpPOJGhRoVRZ9EW7hmKkUHDEMyk+a4weSYiIiIiaiBBEHBDUwx1ggZxlzQo1Oqs+ri7OKBPuAKqcF+0V7iw8Bc1KU1pDo7cOIZfsuJhEH5/Q0cEEXoqovBo+8EIkPvZMMKWi8kzEREREVE9sgvKEJeQhdgEDbJul1q1O0ol6BniA5VSgS7tPSAWM2GmpiMIApILruGHtBM4n5sIAb/fNmAntkPftr0wrP1AeDm2aZJ4TOVlKE6+AmnnDoCzR5OM2RSYPBMRERER1aKoVIdTl7KhTsxCSkaRVbudRISuwW3QV+mLyI5t4GDPwl/UtPQmA+I1v+KHtBNI196yaJNJZBgY0BeDA/rDTSp/4LEIgoDy5GQUnjiO4tO/QKiowC1HR3R6ew0gax2fVc7kmYiIiIjoNxU6I85ezYE6UYOE67drLfwV2s4dKqUC0V184Cyzt0GU9LAr0hXjpww1fkqPRbFea9Hm5uCKwQExGBCggqPdg7/P3lBYiKLYn1F44jj0WVkWbSI7CdCKPn6NyTMRERERPdSMJhMSU/MRm5CFs1dyUaG3LvwV4O0MldIXfcIUaOMms0GUREBa8S38mH4Cp7POWtzPDACB8nYY0q4/uvtEQiJ+sLsgBKMRJRcvoPDEcZScPwcYLWMROzrCTdUXQU/+AeVOTjAYTA80nqbC5JmIiIiIHjqCIOBaZhHUCRqcuqRBUaneqo+nqxR9whXoG+6LAB8XG0RJBOiMepzNPo+fMmJxveimRZtYJEY37wg80m4AglzbP9DidILBgNKkS9CeOQ3tmTMwaout+jiGhMJtwEC49IiGg7MjHD2cUZ5fUsvZWiYmz0RERET00Mi6XQp1QhbUiRpk55dZtTvL7BDdxQeqcAU6t3OHmJWyyUY0Jdk4cSsO6szTKDVYzlVHO0f09+uDgQF94SlrvIJcGRnpeP/991BQUAB3d3eMfXwsTu/bA9/CIgSbTJAK1rcxiORyXBBMOGswQKQtwrT2gXCVShstpuaEyTMRERERtWqF2grEXcqGOiELqVnWq2V2EjG6dfZC33AFIoLbwN6u9dyjSS2LwWTA+dxE/JShxpX8ZKt2P2dfDPDvi96+PSCzkyIjIx2L3l9lTnanTXsR/v4Bdz+uwYC5c1/CkSOHUVqQj2hvH4S09YP4xk08Ym99X3+5wYDYbA2OZN3CL7k5KCsvN7ft2/cphg0bjvXr37vrOJo7Js9ERERE1OqUVRhw5koO1AlZSLyRj5oLZiIAXQI9oFIq0DPEB04y/llMjS8+/hTmzZuL4uJiyOVyrFr1Dnr27GXVL6skG+rM01BnnUaxzrIAmJ3YDj18IjHAv695a7bBYMCsWX/HkSOHkZubY+5blbi+884G2Nk1bE4LRiNWzZ4Bx/Pn8FaXcIS7e8CuliJfpQY9fs7Kwo+ZGYjL1qDcaF0bAAByc3OwZ89uiMUi7Nq1s0ExtBT8vwQRERERtQoGowkXr92GOjELv17Nha6WIkWBCjlUSgV6hyngIW+dW0upUs0tyHdala2r792co7ry8nIMGqRCaup1CNXeuRk1ahg6dAjCsWNqCHYCTmvOIS7ztNW9zADg4+iF/v4q9GnbEy72zhZtc+e+hD17dlucG/g9cQVEWL9+U62xCYIAfbYGpYkJKPnt358qdEBomFXfYp0OJzSZ+PFWBk7lZENnaljhL0EQcOTIYaSlpcHFxbNBj2kJRELNZ9yGcnKst9E0N3Z2Ynh4OCM/v6TVVI2j1oVzlFoCzlNq7jhHWw6TICA5vRDqxMrCXyXlBqs+Xm4yqJQKqMJ94eflXMtZWp6HfY5WT2olEgkAEYxGA9zd3TFlyjSsWbPSalXWy8vbalW2+nbl6n3btPGCq6sriouL6z1Hbfr06Ybr169ZN4gAH6U/Ih6Phm+PdtCbLOerWCRGpJcSA/xVCPHoCLHIegU4IyMdjz46yCKumry9fXD48I/w9w+ASa9Hxc0bKE9JRllKMsqvpcCQn1/nY28UF+OXHA3UGg3ic7NhuI90ce7cuXjjjbea/Rz19m7Y52Bz5ZmIiIiIWpyMHC3UiRqoEzTIKyq3andxtEevMB/0DfdFR3/XB1qFmBq+ynuvK7lV6kp2q/u//9uGiooKq+O1rcrWtYKbl5eLvLzcBp2jpvj4U0hNvW5xTO7njvb9OyNwQAicf0vUqifO/i5toWobjV6K7pA73Lmy+/vvv3fHxNlH5gilnT1Or1oOo8IXFTdvQDBYv6lUpQzAzxlpOJWdjVM52cguty6kd69u377daOdqDpg8ExEREVGLcLuoHHGXKhPmtGytVbuDnRjdQ7yhCldAGeQJOwkLfz1odSWzNe+9bWi/+tSV7FZXW+JcRRAEfP/9YWRkpAMAjhw5fMdz1XeO2hL/efPmQhAEOLZxQft+ndA+phPcO3hZ9TOW6jEkZDD6to1GgItfg9/gKSgoAADIJBIEyV3R0dUNHV1//+rm8NvtCCUlKL+WYvV4kVQGx+BgOIWFwyk8Ass+3IItX35+F89Aw3l6tp4t2wCTZyIiIiJqxkrL9Th9ubLw1+WbBaiZ5ohFIoQHeaBvuC+6h3hB5tB6/ry931XaptDQe2/v5x7dKhkZ6feU7NaUk5ON99/fBEC44wpuQ87x1lvLLI4X67SQKd0xePxYeHdpa/U4wWRC1q9puH7sMqR5Imw5ufaO4wiCAGNRIfTZOdBla6DP0eAJk4CxQ4bD39m5QR+lZq/whWPHjpAFd4Rjx05w8A+AqFpBsGnTZ2LfZ3vv+bmoi4+PD/7xj3806jltrfX834WIiIiIWgW9wYTzKblQJ2hwLiUPBqP1/ZJBbV3Nhb/cnB1sEGXjqVmRedmyt7Fr1456Vmltf831JbNVK7Tx8aca1K+uldwq9W1XvhsFBXXf83u359DqS3AhJxFnss8jKf8qOoyzLryVd1WDmyeTkR6bgvKCUgBAZGQ3CIIAU0kJDPn5MBTkQ59/G/rsbOhzsqHP1kCXnQ2hxkp6ewBwqX1rd05ZGa4VF+GmrgIT5y9EQK8+kNTRt4q/fwCGDRte74r+3RCJRBg69FG0a9cO+fkljXLO5oDJMxERERHZnEkQcPlmAdQJWTh9OQdlFdb3aCo8HKHq4o0+Hd3RxkkEoaICppwMlKZXQNDrIOj1MOn0ld/rdDDp9RB0lccFgwGCQQ/BYPztewMEo6Ha90bAaIRgMlV+X/VVMEEwmgBTZRsEoPJzrwQIpsqvqPpaPe8Qmf9j/gKRCBCJIBKJAbEIAkTIuJUBnV6HeV7eMLXxgiAI0Ly9HI+YBAwMDYMhpAuMgglGkwCDIMCYkoJDL05DdO8+yHWSQW8UIIjFEEnsADs7iCQSiOzsIJLYQWRvV/m9nT1EdpLfvtpBZP/bV/P39hDZ20Fc9X3VcYnkjq9ZQ5LZnJxszJ8/t0H9alvJra5qu3JjcHf3AKz2MTSczMMJsnA3rDu7FckF12ASqr3BIwhw0AswpOajKD4N5UkaSEuN6GnvgOF+wfAOdoS3oyMig4KRPGMqBL3+rsfXA7iafxspRUVIKSpESlEhrhUXoVCng0gkwtNPP4vAR4Y2+HzvvLMBgAjff38YOTnZ5uMikcgioa75s1QqAwBUVPxed8Db2wdDhz6Kdev4Oc9ERERERHdNMBphKiuDsaQEptISGEtLYSwpQW52Pm7cyEFW5m2YysohN+kwwqSH1KSHg0kPJ+jhLDbBAUbgegVwyogiAEW2vqBG4iuVAtK7/MgsoxGFsScfTEDVicW/J9L29r8n17/9PDhLg059+kFnMkFvMkFnMkJvNEFX9b2p8nu51BGhwR2h/62f3mSC4bc2Q9U/QYAsLxflqdcrk3aJpPKNAIkEEEsgEouhkMvhau8AkyDAKAgwQYBJqPxXc8W0tu39YpEIEpEIPt4+mPqXSYAgMBi8cgAAIABJREFU4Mj/vkBhfj4kIhHsxWJIJRI4iMVwqPlVLIGbuzN8O3jD268N3F2d4HC7APZfxiNcL8BBb4KDQYCTDpBVmCAyVUXgB4T61f78FhXdOX2XSGDv5QV7bwUcfLxh76OAvY8PHBS+EHl44v1X/oHvkyyT3arEtTIZbjg7OzusX7/J4lYBDw9PjB37B+zf/1mdP0+bNgOCIFg8Ztq0GfDz84edXeurOcCPqrpLD/vHAlDzxzlKLQHnKTV3nKN3ZqqogLG4CMbiYhhLtP/P3p2Ht3Gfh77/DnYQAAmuABdR+0JStizLkijviWU3cdO6SZs6a7c0lhOndo+dm557zr19Evc2a5P0yI5jZTtJfeJYjpM0TZrEsuQttUVZkmVLIrWLpESQAEESILFvM/cPgBApkCIoUxJJvZ/nwTPgzGAwsEcAXvze3/uSCYWzy3CITDhCJpy9r0bCZCJR1GgENV5YEXvWUpRs4KjPBm2jwRs6BRQdKGRHjxXGjCYrnBtiPjcKreXvjK7T0FSVVDLJcCCATgEd2cBOyQV3ekXBoJt/gYcYT2e1YiivwFBejsFZjqHcicFZjrG6BmNNDcaKyilH/88PdkcD19lgLr2PSqsqIYQQQghRFE3TUGNRMsPDpHO3zPAw6dBINkgeyQbK6dx9LZm8LOelahqxdJq4qqK3WKhpWIDeYkExm9HlborZjM5kQjGZsyOjJlNulNSEYjLy3f/9PXa+/CKJTJqUquVGPDP50c67//gDfOkrXx8zyqkbV0zpUrnjjls4dOjtC+6jPy+Yzt7XYdApvP+e9/P1r3yZ4UCYdCKZTUfPZNPP86no+VT1NFoql6aeT2HPbUulstvS55ZqKjV+v1RqzL7n1ovxFLMZvc2O3m5H73Cgt9kZjEV4/tVXGIpGSRuNfOST99O0fiOG8nJ00804mEB9fQOPPvqlGTh7UQwJnoUQQggh5qlsUBwjHQzkCxKlg0HSwQCZ4DDp4SDpkWygfDHzLqek16OarUQVE8MZPXGdKXvT55Y6M2VVpSxeVMPyJS62/eBJ/uN3/0k4lSKSThFLp/Nprdl5nB+dsiLzWB5PD997adcF59v+54sv8FBg6LJXsQ6Fps64zOTSk7N/ZMZt01VUUNK4gITjyozqaaqKlk7zuUce5Nf//nOMOgWTTo/xvJTnO25/N/d9Ygs//N6T7N2zG6Oiw6gbfzPodFzTvJp33/7uc3PPM7kfA9K5eeeqCqqKmslwtKOdwNAgmVQqn4o9ltFowul0UldXj8/nJZPJoDcYcNfVY7ZYxmQTKKDTk9CSDMaC9EYGSFsgbVDI6BUyOkjrs/fTelCTOpY2rGL1wjVUON3oLFZ0Fkv+NtGPLrXA6oceuUz/V8SlJsGzEEIIIcQcpGkaajRKemiIVGCQ9NBQ7n52ORoon1+p950YSaUYjMcIJhIEEgniOh0JnY6BSJjewBDDySTDqTTOxdfSuP59aOUriKcKA7u6KhutzS5am11UOa1ANtD98Us7GQhNPJu52IrMYxVb0GqqQlWXgsNRXJroRKqra7j//s/M4NlMn6LToZhMfPmbj5NUdOzatYOzE8y9fSjXv/lTW7/NiYcfLChINbrfnxXZ5xlgAePTlQ0GI6CRTqcLUpeXT/D4UDLM0aET2VvgBMHEcG5L6bj9THoTTeXLWV3VREvlKsrMpYUHE1cVCZ6FEEIIIWYhTVVJBwKkBgdIDw5ml0ODpAYG8kHyTATGOrsdQ2kZ+tJSDpw4zpEz3fQEhhhKJBhKxKGkhLTZTPupk6TVyUc4y1xLqW++iwUrb8ZiryAGMCZwdtpNtDa7aW1xsaDGnpsjfM6lCHSLrc48E22LpuurX/0Gd9+9edqtgUZbADU0zI5+z5MVmjp/7m2x+xVrOunKyUyKU8OdHBk6ztGhE3jCfZPuW2mpYHVVE9dUNrGsfAlGnYRL4hy5GoQQQgghrgBNVbPziwf8pAb8DJ4+xdG23VgSCcoUBbumwQWC1alEUin88RgD8TgD8RhhRUfN4iV88G/+FlNlFYYyJ4ayMpTcaN+DD36K7f/+3LSCuZIyN/WrbqW+6VbsFYXBXDoZY0OTizvWL2FlYzk6nTLBUbIuRaDrdDqL3K+86GPOlHXr1rNo0WI6O09Puo9Op0Mdcw1cbCXly6HYYPZyzNFNZJJ0DndzIniaE4HTdI+cIa1lJtzXqDOyzLmYVRXLWV25CldJTcEPO0KMkuBZCCGEEOISURMJUv5+Uv5+kv39pPz+7N8DA6QHBwqKLi0t8riKyYShvAJjRQWG8gp2vtHGy/v34otG8cWi9MdjRCco6KQc2MdBo7Fg3rDH08POnTuKCpxN1lLqVt5M/apbKa9bVbA9k07h79pPz5FX6D+9j0Wf3ELTB6ceKb4Uge6WLQ/w3HPPXnBEu7q6hi1bPl30MWfSK6+0cdttrXR1dRb00l20aDFPP/0cP/rR92dlJeXZJJaOc3q4ixOB05wMnqY71DO+7/IYCgoNjjqaKlawqnw5S8oWYtQbL/MZi7lKgmchhBBCiGkam3paU1rKX/zR+9GGBnljx28xR2NU6HW4TGa0cPiijh9KJumLZQPh0oZGNn/gzzBUVmKsrMZYWYnOfi7t2ePp4Yv/8qUpU55h8nnDU6VM6w1m3Ms2Ut90G1ULr0OnK2yfM3j2MJ6jr9B3/HVSiUh+fbEjxZci0K2vb2Dz5rvYvv3pCX8YGE2BvtzFwkZZLBb27HmL/fv38rnPPUw4HMLhKOVrX/sma9euA5BKyufRNA1/bIDO4TN0jpyhc7gbT7jvXEuwCVRZKlhRvpRVFctZWb4cu8l2Gc9YzCcSPAshhBBCTCETjZLyeYn39fGrp/43MY+HtQYj9TYbzmiM+HefBGBN/gEZtOTk1asVkwljVTUZu51fvvIipwcH6YtG6ItG6YtGiIwZNa7uPM2N/+/nJw3wipkrPNZE84YnSplWdHqqGtdQ33Qr7mWtGIyWgn1G/J14jryK5+jviYcHJny+YkeKL1Wgm01xViYtVDUbUqDXrVvPrl2/v9KnMSvF03G6R3roHOmmc7ibzpEzRFLRCz7GVVLDMudiljuXsMy5mHJLcVkNQkxFgmchhBBCCEBNpbIp1T4vaX8/A0N+Qmd6SPZ5yYypAL0RoMY15fEG43F6oxGM1TXc9Id/hLG6BmNNDcaqavSlpSiKwj/+4//Nk3v3XPA4UxXJKnau8PjHjB8NHpsy7axdQf2q26hbeRPmksKgIzbix3P0VTxHXyU00H3B55nuSPGlCHRnulCVuHRi6Tg9IQ9nQx7O5G79Uf8FR5UVFOrsbpY5F7MsFyyXmi6+krkQFyLBsxBCCHGJaZpGSk0RzyRIpJMk1SQpNUUqkyKppvP3U2qKpJoiraZJqxkyWoaMmiGtpVFVlXTu74yWQdVUVE1FQ0PVtNxSzbYvQmXcd01ldKGM/RNFUdChQ1F06BQFnaLL3jj3t16nR6/kbjo9hjH39Yoeg06PUWfEoNNj0Bkx6gwYdQYMOsOYv42Y9EZMehNGnQGdUtgLtVhjAyCn08mWLQ9MayRS0zQyw8MkvX25m5ek10vK10dqYACmWfnYF4viiUToCYc5GwnjiUTwRMP0RiLEcn15q6tr2PGPX6BygvOciSJZxc4VHv+Y8aPBH/jQJ2k7Ead84Q3YnLUF+yfjIfqOv47nyCsMeY7ABYKZURczUnwpA93LUahKFC+UDOMJ99ET7s0Fyz34o4MXDJQBbMYSFpc2srhsIYtLF7KwtAGLoTArQohLQYJnIYQQYgoZNUM4FSWSihBNx4imosTS8ez9dIxYOkY0FSOWjhNLx0hkEiQySeLp7DKRSUz5hfBqYtAZMOnOBdMmvQmz3oRJl1vqzZj1Rsx6c36bUTHw3PbtHNz/FkP9A6RiKdLxFL/a+Stu3nQLX//y/8JkNOWfQ0unSfb3k+zrzQbJfb25INmLGotN63z1ZU5MLhcHe86wY+8beCIRzkbC9EYjJDITV/Ad60IjxzNRJKuYucJjjY4GD4cT7DnSz+52L93eEA1r/mjcfpl0At+pfXiOvoK/600WNjaiT4YZGzhXV9dgt9sJhULjnv+dpkRLoDt/JDNJ+iI+esNeeiNeesNePOE+Qqmp6wEYFD11djeNpQtYUrqQxWWNVFurpBq2uGIkeBZCCHFViqfjDCdDjCRGsstkiFAyTDgZJpyKEk6FCScjhFIRYunpBVviwrIj62mi0/3vus7KNes2jVtlSqmUD2f4zo8eoSqkUTWi4hxJYx9JopvG7xWK2YzR5cLsrsPkdmOpq6Vq+WLiJWVoRjMAX3vwUzxz6sT0zjlnspHjmSiSNdVc4bGM5hJufd/f8szv/XR0Hy8caNc0hr1H6Dy4E++J3aSTMaqra/jzD97LN77xGD6fd8IRYUmJFtFUFG/Ujy/Sjy/qxxvtxxfpxx+bejQZsj+q1dtqWVBaT6O9ngWl9dTZ3Bikz7KYReRqFEIIMa9omkY4FSEQDzKUCBKI526JIMOJECPJbLCczCQv2TkoKFgMZsz67M2iN2PWmzAbzPkRVqPeiGk0rVlvzKY264wY9cZsyrOiR68zoFd0GHLLbNp09r5O0WfTrhUFhWyK9bk0bCWfoj06Sqjl/9Lyq0dTvbM3DQ2VjKai5f7OaCqqlk0TH5tGPvbvtJohnUs1T+Vuo8FxSk3l1qVIZrIp6dlU9WRumf07oSZJq4VtlcayxFUqRtJUDGdyyzQVIxkc0eL7IGvAiE1HoNRAoFSfuxkIOPRErDpQ4uiULqx6L9bUURyn3sCkmLDoLVgNVozrSmlOrSMZTZKKJEhFkiQjCVLRBMlIklQ0QTo2cZGwyUaOZ6pI1mRzhQEUnYGaRWtZct1dVC68noSip71rfDC/0OWgtcXFhiYX0ZGVbNvmIXhNbUEgPNmIsIwUXx3i6QQDsUEG4kMMxAbpjw7gi/bji/iLGkkeZTfaqLPXUm9zU2d3s8DRQJ3NhX6CKu5CzCaKVkxDv8vE7w9d6VOYksGgo7zcRiAQIZ0u/gNbiMtFrlExF7yT61TTNCKpKP7YIIO5L3H+2CBD8SCBeIBgYpjUFIFYsawGCzajDYfRhs1ow260UWK0UmIowWq0UGKwZm/G7NJqsGI1WDDqjJJWOE0ZNZNNdQ8MEus9S7K3l1RfH5qvn3h3D9ZM8ddJWq8QcOgZKssGx0OjgbLDQMZwaf+/aKpKKpoLqnPBtS6tsPn2O6kqq8pfM6PXSonRikkx8ZV/+mdefuEFfL3e/LHGpj4bDMWNd4yOAAeCQRSri6RlAUlzHejMBftWlVlobXGzqcVFbaW07plrLsXnfVpNE0wMZ398jAfxxwYZiGUD5YHY4LQCZACjzoDb5qIuFyTX22ups9VSarLLe+RVYC59J62uLq7InATP0zSXLgJxdZJrVMwFU12no6PHvqgfX7Sf/uhA7svbEAOxIeKZ+EU/t9VgodRUSpnJQanZQZmplFKzg1JT9uYw2bEZS7AbbZIueIlki3YFSXg82bnIvb0kej0ke3tRo5GpD5AzkkzSFRqhKxyiOxRi4bobeOgL/4yhohIUJRuMZ+LE0wli6TjxTDy7TMdz89Nz9zPZZTQdJ56O5ZbZ+esZ7TK/j6pAUkWv6nBVuCkrKc0G2/kfaLKj4CUGC5bc0jpmff9gnD1H+mlr9zE4UvjvxG41sqGphtYWN0vrSiWAmcOm+3mfUtPnpqkkRgiMBsn5DJ0AI8nwRdVnKDU5cJVU47LV4C6pyd4vqabc4nxHBQLF3DaXvpMWGzzLtwIhhBBXjKqp+CL92blxUT++iD8fME97Pixg0ZsptzgpNzsptzipGHO/3OykzFyKSW+8BK9k9nmnValnwrgguTcbKI8GzGr0wn1ax4rpdLT7vHSHQ3SFQvmAOZBIjNvv/rveg7GqOv+3xWDGYjBD4aDrlAwGHU5nCb6BAKFErkBcKkY4GeG7P9zGsdNHSagJjCVmTDYzFocVY4kJvdWAyWbGWGLCZDOj6KcZOOgAi44M0Bv30hv3TvWIcTRVgYwRbZEBc8aAljag04xU2OzUVzipr3BSYvTiU4KM+K1Y9GYsBgsWvRmrwZKfbiABz9yQSCcZjA0RjIUIpyKEkxHCqQihZJiRZIjhxEh+GUkX/29uImUmB1XWSqqslVRbK6m0VlBtrcJVUk2J0TpDr0iI2U1GnqdpLv2CIq5Oco2K2UjTNIaTI3jCXvoi2Zsv1k/PSN+0Uqx1io4KS3n+i1uVpSL/Za7SUn5VfYGbLDhOp9M8/PDfsXPnjnFFqKqqqtm8+a5ppQAXa7T9U3b0OHu7mCDZUF6Bqa4OU20dpro6zHX1mGrr8AYD3HnnbVMW1dqx4+UZ+4FgqvfSiQpkaZo2bt19932KSld1thp7OpYLwAsrtcdS8XNV28dUbn8nGRbvlFlvys7VN4zO2c/N38/P5T+3/VyVdFO+Orp5zP3sXH4Thtw8fXFOWk3nW9glMonc/QTRdDR/LYyt6D963URSUcLJMEl14jn2F6PU5Mj+6Dj6g6PFOeY9tgKT3jT1QYQYYy59J5W07UtkLl0E4uok16i40jJqBl/Un+/b2RPupTfsndZIcrnZmUsBrMaVSwGstlbiNJfN+4Iy5wfF99zzAX75y5/n//7EJ7bw9a9/ZdLgWFVVfvrTZyYtPnXvvR9l69YnLvr80iMjueC4JxcoZ0eTp5NubaiowFRXnw2O88FyPXrr5D9+PPjgpy5YVOveez/C1q3fvqjXNOE5zoL3UlVTc+nk2YApFI9ypKefo55+egaDqLoUij4NhtxSn8Js0TCZVVTd7GuRpqCMKZSX7f09ujQoBgx6A0Yl2yN8tHd4dmnI9RXXYVAM6HS6fI/xfA9yZbRfue68Inq5nuW5QnqF5zSemuuTrmnamD7qo/3TNVQ1k++3nl2mx/VfT6uZXCG8ZHappscUycsWzxsbJKe1qVudvVMGnYEyUyllZkd2yoo5O22lzFxKhaWcCouTMnMZRpmmImbYbHgfLZYEz5fIXLoIxNVJrlFxOWXUDL0RH2dDHs6Gejgb8tAT7iNVxGiIoijUWKuos7mptblw2bJBck1JNearcIRjshFjRVHGBYxms5nEeenKY021vdgR2kw4nB1J9nhI9PaQ9GQD5Uy4+M/qgiA5N5J8oSB5Mtn/Pg8WVJO+mKJaRZ37LHkvVVWNY2cC7O7wsf+Yn1iiMFPDVVHCpmYXG1tcuMpL8us1TcvP+46Nm+c9OrKdIJ5O5OeFx/Pr4sRyy0Run9kUhF/tdIqOEoMVh8lOeUkpFl22iKHDaMNutGM3ZYsbjgbJVoNVRvzFFTFb3keLIXOehRBCzLhAPEjnyBk6h7vpGjnDmZBnyhZDAGWmUursuWqrtloWlNXSVL+YSCg16z9QL5eHH/67CUdWz//7QoFxMdv9/n62bXuCRx/9IgCZaPRcmnU+5bqHzMhI0eeudzpzAXI95vrscqqR5OkyGAxs3frEVdFPWNM0zvjCtHV42dPhIxgubKtWajOxoamGTS1uFrkdE4+qKkp+3rfTXPaOzielpklkEvlgOp5JkMhkR7eTmSSJTPK8ZYJEbsQ1mUnm25Wl8u3KUvl1mcsw+jpbGHXGXFr7uRT4senxo/fzVdlzheLGVvU3680oijKnAhMh5gsJnoUQQkwolUnRHeqha+QMncNn6Bo5QzAxPOXjqqyVLHDU0+ioZ4GjngX2euym8W1wDAYdJoOJCDM3X+9K8Hh6ePTRf+Sll3ahqhlqa+v413/9FuvWrZ/2cXbu3DFhSvJMseoNLHY4WOwopaW/n55v/gvJXg/pQGDqB+foS0tzAXLDuBFlve3ytTmaz/2E/cEYbR0+2tq99A0WzhU3m/SsW1FNa4uLpoXl6HWXp6iXoiiY9Nn0agf2GT++qqn5PuHnlilSuR7iKTU9rsd4RlPzadPqmHWjPctHU6y10XW51OvzTTYFQKfo0KGMuZ/rna4oY9LFDbmlDn2+L7seg6LP920fTUkfTVM36AwyAizEHCfBsxBCCADi6QSdw92cDJ7mRLCT7pEzU87Hq7ZWsrB0QT5YbrDXz6uiXRcqyvXQQ5/mZz97FlU996V8ZGSE9773DhYtWsyrr+7BYrEU9Tzbtn3rgsWwpsOi17PIUZoPlEdv7pJz6byk00TbD096DL3dkU2zrq/HXNeQW9ajt8984HS1C0WT7Dvaz+4OHyd7Cn+c0usUrllSSWuLizXLqjAb59+cf52iyxcbE0KI2UyCZyGEuEpFUzFODXdyIniak8FOzoY8E47OjLLozSwsXcDi0kYWly1kYekCHKb5GUxNNv/4ueeeHVeUazJdXZ3cdlsre/a8VdTzBYPBaZ+jRa9noX00QHbkAuZS6qYxCqwrseXSrOvGjSgbSkunfT6ieIlUhrdODNDW7uVw5xAZtXAEdHlDGa0tbtavqsFuvTraqwkhxGwnwbMQQlwlUmqazuEujg6d5OjQCc6Eei5YBKjKWsmyssUscS5kcelC3Laaq6b362TzjwcG/DzzzI8xGqcOZjo7T7N//96iUridTuek2yYLkt0lJeiKTAENp1J0hkboCoVwLlvOh/7u77MjyWVlkkZ6mWRUlSNdAXa3+3jzhJ9EsjCro67KRmuzi9ZmF1XO+ZPBIYQQ84UEz0IIMU+pmkpv2MvRwAmODp3gZLDzglWw3TYXy5yLWe5cwjLn4ndUYGg2mCzlupjHTTX/OJUqbq72P/zDI+zc+eqU+23Z8gC//vnPsCcTLHI4WGy/uJHkSCpFyGRiSKdjz6kTHOrrpTMUwh+P5atSP3QJ+jyLiWmaRpc3xO52L28c6WckUlj4q9xhZmOTi9YWFwtq7PJjhhBCzGLy6SmEEPNINBWlY+g4hweOcnToOKFUeNJ962xuVpQvZblzCUudi+d0CvbYQLm0tIy+vl52735twpTrqVoazeT841CosGJ1Jhoh2dd3rkdyXy/J3l6eab2x6ONG0ym6wxFOjwTpDI3QORJi2GTkuptv5RvffByDwcD63H+TJfO4KvVs5QtEaWvPFv7yBQr7m1vNBm5YWU1ri5uVC5zodBIwCyHEXCDBsxBCzGGaptEX8XF48AiHB47SOdI96bzlMlMpqyqWs6piOSvLl1NmLq6n4Ww22dzkiQwM+Nm+/WlAYevWJybd72LmH0+k3Gzm+uoagi/tItnXS6K3l2RfH5nh4o8fSaXoCofoHBmhK5wNkkdMJtbcfAuPfOGf2f/9bRAMcv0EwfF8rko9Gw1HkrxxxEdbu4/OvsIfTQx6hWuXVtHa7GLNskqMhvlX+EsIIeY7CZ6FEGKOSWVSHAuc5PDgUdoHjzIUn7jVkFlvYkX5UlaWL6epYjmukppZmRLq8fTwL//yFfbt24Omwfr1G/jsZ/97USnWk81NnoymaezatQOPp2fS419o/vH5FMBdUsJCuyN7czhYlFuWmcwA9P/4qSmPo7Nac72R64iX2Pjt3jbORqMY6+q4508+wIF//9mEQbIEx1dWPJnmwPEBdnd46egMoJ53HSrAykYnrS1u1q2sxmaRwl9CCDGXKdqlbCo5TX5/6EqfwpSkIb2Y7eQanZ/i6Tjtg8d423+Y9sGjxDOJCferKalidWUTLZWrWOZcjEE3O38jNRh0OBxmPv7xv+QXv/gZicT412M2m7nnng/wr//6rUlTrD2eHu6887aLSrG+//7P8OijXyz6uCadjnqbPR8YLy5zsqCkhEabHcs05g/r7Q5MtbX5QNlcV4+ptk4Kd81Ck72XpjMq7Z1DtHX4OHDCTzJV+D67oMZOa4uLjU0uKkqLa1cmxHTJ572Y7ebSNVpdXVw23ox+q+ro6ODLX/4yHR0dmM1mNm3axP/4H/+DioqKmXwaIYS4KoRTEQ4NHOFt/yGODJ0graYL9tErepY7l7C6Khsw15RUXYEzLVRMsa5PfvKTPPPM0xM+PpFI8OyzP0Gn00+aYv1O5iYHgxOP1mfCYSqiMR68/d34jnTQaLOz0OGgtsSGfhrB7WAySf21a7A0NGCqrcvdajE4pAXUXKRpGqd6R2jLFf4KxwoLxlWWmtnY7Ka1xUVD9dytHyCEEGJyMxY8p9Np7rvvPj7wgQ/wve99j0gkwiOPPMLnP/95tm7dOlNPI4QQ81ooGeYt/yEO9B/iRPD0hPOXSwxWrqlq5trqFlaVL8NimD0jW1P1Rx4t1tXT08Ovf/3rKY/3/PO/mTTF+mLnJusVhQV2B+G3DpD09pH0ekl6+0h5vWTC2QyodwMsXX7hA+l0KOUVnBgc4MCZbs5EwsRtNv7+n77Epo2bLurcxOxy1hfid693svtwH/5gvGC7zWJg/aoaWlvcLGsoK7p1mBBCiLlpxoJnv9+P3+/nnnvuwWQyYTKZuPPOO/nBD34wU08hhBDzUiwd56C/nX2+tzgaODFhwFxmcrCmejVrqlez3LkEvW52Fhu6UH/kscW6nnzycQYGBqY8XiAwxLZtT0yYYj3V3OQyk4kFNjuNdgeN9uxygd1Og82Osb+f3sf/V1GvKaUoBBSImC2s3HQjlStWYaqtw1hTg85oZDlwd1FHEnNBIJTgjSM+9nT46PIWTiczGnRct6yK1hYX1yypxKC/OnqfCyGEmMHg2eVy0dTUxPbt23nooYeIx+Ps2LGD22+/vehj6HTKrG/XoM99SOrlw1LMUnKNzg3JTIpD/g72et/i0MCRCVOyq6yVXO+6hrU117CobAE65fL/P+3p6eHJJx8nEAhQXl7O/fd/hoaGiQtt9fT0sGvXC5MW79I0jRdf3IHX2zutUeORkSAGQ+Fr//Sn/47/+PlzmGNRFtgdNNrs2aXdTqPdni/YVSyDsxxTrRtzbR3m2lpMtXWY6+owlJfLfOR5LhpPs+9oP68f9nKka4jzr2BFgZZFFWxa7eZK4N40AAAgAElEQVSGVTVYzbOzloC4usjnvZjt5uM1OmPv/jqdjscee4y/+qu/4kc/+hEAGzZs4JFHHin6GBUVtjnzBaW01HqlT0GIC5JrdPZRNZXDvmO82rWHvZ63iaUL00CrSyq4sfEGbmq8gYXOhsv2nnj27Fm++c1vEggEMBgMZDIZXn31VXp7e4nFzvWpfe65Z7n77rv57ne/W1DI65/+aRt+f/8Fn6e/v58f/vA7uFzVRZ+b21WNNRUh3ttHzOMh5ukj1ttLwtPL9tabmM5/oTTgaGykpKEea0M91vo6rPXZpaGkZBpHEnNdKq2y/6iPl9/s4Y12L6kJitksayjj9nULuOW6ein8JWYt+bwXs918ukZnrNp2Mpnk/e9/P7fffjv3338/0WiUL3zhC+h0Oh5//PGijjE4GJ4TI8+lpVZGRmJkMrO7apy4Osk1Ovv0Rwd43bOXtr79BOKFI64Ok511rjVsqF3LkrKFl/VHxHQ6zUMPPcDOnS9MGfiOUhSFD3/4ozz++JPj1j/wwBZ+8pMfT/n4j3zkY/zP//mP3HbbjeNSt50mM412OwtsdhbYs7eFpWUsKnNCunBk/kIGEwnCZhPxkhL86TTp0lL+6C//hoaWFhTd/PkFXEyPqmkcPxNk92EvbxzxEYkXXlc1TiubVru5eU0dq5ZUyXupmLXk817MdnPpGi0vtxW134yNPO/evZuenh4efvhh9Ho9DoeDBx98kHvuuSdfbXUqqqqhqrOmc9YFZTLqrC+5Lq5uco1eWbF0nAP9B2nr28ep4a6C7VaDheuqr+EG13Xj5jBnMhoUJI1eOg8++MC0+iRDNv36hRd20N19Zlwhr7Kyqd/n7QYjiy0llHR28Y/v3szgyVM02Ow02G04jKaJHzRJ4KyzWDC6azG5XMRLSnjxrTfxxGIo5RV84lOfyfdCHiujAqr8u7ja9PjDtLX72NPhZXCksM2bo8TIhlUuWltcLKkrRVGU/FQBeS8Vs51co2K2m0/X6IwFz5lMBlVVx30BSyaTM3V4IYSY9TRN43jgFLv79vGW/xApdXw7G52io7liJa21N7C6qgnjJezBXEyrKI+nh507d0wrcB7l9/cXFPLasuUBnnvuWSKBIept2XnHDbbcLTeiXG42w8AAnu88yfUADQsu/ER6PaYaF0aXC5PLjcnlxuh2Y3K50JeO7438iY/+xbRfh5i/hkbi7OnwsbvdR48/XLDdZNRx/YpqWpvdNC8ql8JfQgghpjRj39zWrl1LSUkJjz32GPfffz/xeJxvf/vbrF+/vqhRZyGEmKvCqQhtfft4zbOH/lhhBelam4vW2htY77qeMrNjxp53NED2eDx0dXWyaNFiamvr6OvrZffu1y7YKgreWZ9kk06HbmiQ0Jv7Sfl8JPu9qD4fP77pFmzTjcUVhRHgTDiEL5nE7K5l859/CHdzC8aKShT97KwsLmafSDzFvqP9tLX7OH42WJDDoVMUWhZXsKnFxdrl1ZhNcm0JIYQo3owFz+Xl5Xz/+9/nK1/5Crfeeismk4kNGzbw+c9/fqaeQgghZg1N0zg13MV/efZwwH+woFp2icHKDa61tNauo9Exc4W/PJ4evvrVL/GrX/2CcHj8aNqhQ29P+rjzW0XB1H2SDYpCbYkt395pQW70uMFmp8ZqRRdP0PfEY+Mec6EZQ2EFqpavxOx2Y3a7qVi2iJTNiVJRic5o4oYLno0QE0ulM7x9cpC2Dh8HTw2QzhT+erO0rpTWFjfrV9VQaptkeoAQQggxhRnNGVy9ejVPPfXUTB5SCCFmlVg6xh7vm/yXp42+iK9g+4ryZdxct5Frq1tmLC3b4+nh299+nB07fsuZM92oFzlnV9M0du3agcfTQ319A06nEx3gLinJp1fnA2S7Hbe1BMM0i2vpHQ6MNS7SDgd7T53Em0iglZXxwfs+xYrFS/L7GQw6ysttBAKReTMPSlw+qqpx7EyA3R0+9h/zE0sUzot3V5TQ2uKitdlFTblUUhdCCPHOSaNCIYQoQl/Ex0tn/4u93jdJnjeX2WYoobX2Bm6q34irpPgWTFNJp9M8/PDfsXPnjotOrx5VabZkA2NrCXu/+iVYvoKPJ9Pc+74/wTjNAHkkmSRqMbN8fSsm17n5yMYaF/ox7Z6WXOAYQkyXpmmc8YVp6/Cyp8NHMFxYV6XMZmJDU7bw1yK3Y860vxRCCDE3SPAshBCTUDWVjsFjvHT2vzgaOFGwfWnZIm6ub2Vt9TUY9cYZf/6HH/67aVXCtuoNNNqzhboW2B00jmn5VGIYc36RCJG3DgBMGjhHUil6ImHORsL0hCOcjYToiYSJWaxsuO1d4+ZOC3Ep+YMx2jp8tLV76RuMFmy3mPSsW1FNa4ubpoXls77lpRBCiLlLvvkIIcR54ukEbd59vHL2tYICYBa9mY2167i5rpU6u/uSncNklbBH06wb7Y7czZ5fVlms03oOxWDAUFPDUZ+Pt890cczfz9lwmJ5ImKHEuXY+VqsVt7uWu/78I3xqkhZQQsykUDTJ3lzhr5Oe4YLtep3CNUsqaW1xcd2yKkxGKfwlhBDi0pPgWQghcgZiQ7zS8xq7+/YSS8fHbauyVnJ7w0201t6A1WC55Ofy/W8/RkUqxdr6BhrtDhbaHTQ6HCyw2TFPo/p0RtPwRiOcDWdHkQMoPPj5f6K2ZTWG8goUnY7FwLW5yt2OYJA1RiOappJOZygvr2DLlk9LwCwuuUQqw1snBmhr93K4c4iMWphxsbyhLF/4y26d+WwPIYQQ4kIkeBZCXPXOhnp5ofsl3uw/iHZec5sV5ct494KbaalchU6Z+T6wmUiEZG8vyb5eEn29JHs9JPv6+NDQIB+67d1FHyeQSHA2HOJMOMyZSIiz4TBnwmF6oxFSuQJjiqJw770fofHW2wseX1/fwKOPfmmmXpYQRcmoKke6Auxu9/HmCT+JZKZgn/oqG60tLjY2uahyTi+7QgghhJhJEjwLIa5KmqZxIniKHd0vc2To+LhtBp2BDa613L7gZurttZMeY7TPcjAYxOl0smXLA9TXN0y4byYSIeHpIdnrIeHxkOzLBsyZ4cKU1MmkVZWzkTBnckFydziUD5hDqdQFH1tdXcMdd9zJN77x2AX3E+JS0zSNLm+I3e1e3jjSz0iksPBXucPMxuZspewFNXYp/CWEEGJWkOBZCHFVUTWVg/52dpx5me6Rs+O22Y02bm+4iZvrW3GY7JMeY7Iq2M899yzvueNOHn3oETJeL0lPD4leDwlPD5kpeiqPpbNaobKKHfv3cnzQT3coGzD3RiNkiigeVl1dw6ZNN+J21zIyMiKp12JW8AWitLVnC3/5ArGC7VazgRtWVrOpxc2KRic6CZiFEELMMhI8CyGuCik1zV7vm+w88wq+6Pi2T5WWcjY33kZr7XpMRVTNHq2C7bJYudldy9LSMpaVlrGstJT6aIzeL/9zUeekd5RiqqvDVFuHqa4Oc232vr6sDEVR2Prgp9j+xu6iq203NCzgD//wj6Wol5g1hiNJ3jjio63dR2ffSMF2g15hzdIqWltcXLu0EqNBCn8JIYSYvSR4FkLMayk1ze7evTzf/SLBxPgU6Xp7LXc13s7ammvR6yb/0q6l09kR5O4uBo908G6vl796z/uwG4srWKSz2TDXN2Cqr8dcN7qsR2+ffHQbyKVYK+zatQO/vz+/3mKxYDAYMBgMVFRUcuONt/DZz/6DBMxiVogn0xw4PsDudi8dXQHU8378UYCVjU5aW9zcsLKaEosU/hJCCDE3SPAshJiXLhQ0L3cu4c6F76K5YgW9vR6+8Pn/Jz9v+b6//iSVqkriTDfx7m4SZ7pJeHogc66QUXNp2YTPGU+nOR0a4fTICO5rruWev92Cub4efWnZRc3ZNBgMbN36xLi51ZKCLWajdEalvXOItg4fB074SabUgn0aa+y0trjZ0FRDRemlr1gvhBBCzDQJnoUQ80o2aH6D57tfKgiaV1c28Z5F72Zx2ULS6TT/7cFPcaptN7UKNDnLaXKWE/r/vkC0iEDXF41ycmSYkyPDnBoZ5sTwMJ5ImNGQ4UNNTXykuWVGXpNUwhazkaZpnPKMsLvDy94j/YRjhUXrKksttLa4aG1xU19luwJnKYQQQswcCZ6FEPPCVEHzexfdQV3MRLzjNP2dv+foy7v4RCqNec3aCx9YUTDV1mJuXIilcSFP79rBN/7Pj6asbu10lr/TlyTErNQ7EKGtw0tbu4+B4XjBdpvFwPqmbKXsZQ1lUvhLCCHEvCHBsxBiTsuoGdq8+/hN585xQbM+rXFjpo4N8RrMh/uJ/eArdEUi+e1uAP34ec5pVeV0aIRjwSC9mTQPffGrNKxdh85szu/zJy2r+davfkloYHzRsbGqq2vYsuXTM/YahbjSAqFEvvBXty9UsN1o0LF2eRWtzW5WL6nAoJ/5nuhCCCHElSbBsxBiTtI0jQP+Q/z69PP4on5KYhmW+VPU+lMsDRoo80dA9ZMG0pMc42w4REcwwJFAgCPBACeGgyTVc3M1bb/5NY+23jjuMfX1DWzefBfbtz89YRVsRVG44447J+33LMRcEY2n2X+8n7Z2H0e7A5x/tSsKNC+qoLXZxfUrqrGa5SuFEEKI+U0+6YQQc87RoRM8f/CXcPoMLf1J/sCXojyUueBjdHY71iVLsSxZyg9++2ue/PefTZl6HQwGJlw/WRXs6uoa7rjjztx2IeaeVFrl0OlB2tq9vHVykHSmsPDXIreD1hY3G5tqKLObJziKEEIIMT9J8CyEmBPSwQBnDrxG54HfYz87wHunCJaHFIWFN95EyfKVWJctw+hy5yteh97YPWXgDJPPW5Yq2GI+UTWNE2eD7G73sf9YP5F4Ya5GjdOaL/zlrii5AmcphBBCXHkSPAshZiU1kSB67CjRjsOMHHob1Zcd4V0wwb4pVeVIYIi3Bgc5NDTI4cAg4XSae61Wtv713xbsv2XLAzz33LMMvMN5y1IFW8xlPf1hdnd42dPhY2gkUbDdUWJkQ5OL1hYXS2pLL6rdmhBCCDGfSPAshJgVNFUl0XOWaPthIu2HiZ88gZaeeLZyRgep2hr+Y88+XjvTzeHAEIlM4Uj0rl078Hh6CuYfy7xlcbUaHI6z54iPtnYvPf5IwXazUc/1K6pobXHTvKgcvU4KfwkhhBCjJHgWQlwxmWiEyOFDRN5+m2jHYTKhwiq+AKoC3koDXU6Fvaf7MFkasGUUvvPmvgse3+/vZ9u2J3j00S8WbJN5y+JqEY6l2HcsW/jr+NlgwXadorB6Sbbw19rl1ZhN+gmOIoQQQggJnoUQl1Wyv5/I2wcIv/0WsRPHYYIRY4Bhm47uWjNnak10OeHg84c49uO3yCTSKIrCokWLi3q+yYp+ybxlMZ+l0hnePjnI7nYvB08NklELMyyW1pfS2uxmfVMNpSWmK3CWQgghxNwiwbMQ4pLSVJX4qVOE3z5A5OBbJHt7J9wvqcCpUvAut9Nda2LYrgdFoeuVYxx65g3igXMpppqm4fX2FfX8kxX9GiXzlsV8oaoaR88EaGv3sf94P7FE4Q9TtZUltDa72NjipsZpvQJnKYQQQsxdEjwLIWacpqrEThwntG8v4f17yYyMTLifsboa0zWrecr3Bj0tVjTDufmV/qN9vP1vrxM4PXFRr1gshsViIR6PT3oexRT9EmIu0zSNM74wu9u97DniYzicLNinzG5iY5OLTS1uGl12KfwlhBBCXCQJnoUQM0JTVWInTxDe9wah/fvIDA8X7qQoWJYsxb7mOkrWrOEN9Qy/PPU74m5bfpewb4SDT7fh2XN6yuesra2jq6tTin6Jq05/MMaedi9tHT76BqMF2y0mPetWVtPa4qapsRydTgJmIYQQ4p2S4FkIcdGyKdknCe0dDZgLixEpBgMlq6/BvvZ6bNeswVBaSudwN9859jPOhs+lcKeiSY784k1O/O4QaurCPZxH3XXXexgeHpGiX+KqMBJNsvdIP20dXk55CrM59DqFa5ZUsmm1mzVLKzEZpfCXEEIIMZMkeBZCTFuyv5+R3a8R2v06qQl6JWeAbr2OXkcpd33qM9QvXQZAKBnmP478lNf79o7bv+uVYxx8uo3EcKzoc6iuruH++z9DfX2DFP0S81YimeHAST9t7T7aO4cmLPy1oqGM1hY3N6yqwW41XoGzFEIIIa4OEjwLIYqSiUYJ79vLyO7XslWyz2cwcFpT+fcjHfzu5HGiuR7N//KbX3HH5rv4089+lP/seoFo+lyAXG+vJfR7H3u//dK0zuX8lGwp+iXmk4yq0tEVoK3dy5vHB0hMkIlRX23LFv5qdlFVJoW/hBBCiMtBgmchxKQ0VSXacZiR118jfOBNtFRq/A6KQklzC6Wtm3j06ad46tmfFMw/zpQpDFwb56cn/yO/zqK38L4ld3Fr/Sa89X388vs/ZWCCEeyJSEq2mI80TeN03wht7T72HvExEk0V7FPuMNPa7KK1xc2CGvsVOEshhBDi6ibBsxCiQDoYZPj3rzD86iukA0MF2011dZRuuhlH6yaM5eV4PD38ZtcL4wJng8XI6ns3sOwPVqOMKVa0wX09f7L0DykzO4DsqPHmzXexffvTkxb+WrFiJWvXrpOUbDHveIeitOUKf/UHCqctlJgN3LCqmtZmNysaneikUrYQQghxxUjwLIQAsiNfsWNHCb78IuEDb0JmfKqozmajdGMrpTfejHnhonHtbrZt+9a4kePa6xu5/m9uoaTKkV8X7B6kcaiGv3zkQwXPnR1FVi5Y+MtgkLcrMT8MhxO8kSv81dkXKthu0OtYs6yS1mY31y6txDimhZsQQgghrhz5NirEVS4TjTDy+usMv/wiSW/f+I2Kgu2aaym9+Vbs165BmSSADQazVbbNZVau+8ubaLxxWX5bOpGi/af7OPGbg9z75x+Z8PEGg4GtW5+Qwl9i3ool0rx53E9bh4+OriHOT7JQgFULy2ltdrFuZTUlFin8JYQQQsw2EjwLcZVKeDwEdj5PaE8bWjI5bpveUYruurU8e6wDz8njOAf62eJyTdozucxZxqLbV7LmY5sw2S359b6DPez/3itE+rOja05n+QXPSQp/ifkknVE53DlEW7uXt04MkEyrBfs01thpbXGzsdlFucN8Bc5SCCGEEMWS4FmIq8hoavbQ735L9PDBgu26hYt4ORjgB6+9iufn24nFzs3BfO65Z9m8+a6CFOr+qB/H3XWsv/1d+XWJkRhvP7Wb7t+fq8pdXV3Dli2fvkSvTIjZQdM0TnqGs4W/jvYTjhUW/qoqs7AxV/irvsp2Bc5SCCGEEBdDgmchrgJaJkN4/z6Gnv8tie6ucdt0Fgv21ht5su01nv3JU5NWvR4Y8LN9+9OAwtatT6BqKi+e/T2/Pv08KTWd36/798d5699eJxmK59ed31pKiPnGMxChrd3Lng4fA8Pxgu12q5H1q2pobXGxrL5sXM0AIYQQQswNEjwLMY+piQTD//UqwRd2kDovKDZUVlJ+5x9QdvOt/P3n/hvbf/rMhNWux9I0jV27dnCo8zA7hl7h9HB3fluFuZzgS710Pnt4XOAsraXEfBUIJdjT4aOt3cuZ/nDBdpNBx3XLq2htcbN6cQUGvRT+EkIIIeYyCZ6FmIfS4TD9v/gFQztfQI1Exm3T1dbyaizG29EIZa++xD3l5ezcuWPKwBkABcpucPHkyX8D/egqhdsX3MQfLXkP5ptMeP5ain6J+SsaT7P/WD9tHT6Odgc4/1+NokDzogpam11cv6Iaq1k+ZoUQQoj5QtGK+sZ8efj9hS07ZhuDQUd5uY1AIEJ6guIvQlxJmWiUkRdfYOiF58lEouO2WZtb+MmpE/zwpV3jUrOtVuu4uc2TsdU4uOH+d1HTXJdfV2Wt5ONNf84y5+KZexHiqjCX3ktTaZWDpwZp6/Dy9slB0pnC811c66C12c2GphrK7FL4az6YS9eouDrJNSpmu7l0jVZXO6beCRl5FmJeUOMxAjtfILDjd6jRMUGzXo9jw0Yq7nov/9fXvsj257YXjDAXEzgv2dzMmo9twjCmfc5tDTdyz9K7MetNM/Y6hJgtVE3j+JkgbR1e9h31E02kC/apKbfSmiv85a4ouQJnKYQQQojLSYJnIeYwNR4n+OJOhp7/7fj0bJ0O5823UH73+zBWVePx9BSfmj2GtdLO+i2347r2XKGv2GCET1z3MW5avmmmXoYQs8bZ/jC7c4W/AqFEwfbSEiPrm1xsanGzuNYhhb+EEEKIq4gEz0LMQWoiQfDlFwn89jdkwmOmOygKZTfdzNKPfYi4xZFPkdm27VuTVtGezIIbl7Hub2/BWHIuBfXUzg6Wxxdw0wclcBbzx8BwLFv4q8OHxx8p2G426rl+RRWbWtw0LSpHr5PCX0IIIcTVSIJnIeYQTVUJ7Wlj4OfPkQ4MndugKDhaN1H5vj+mpL4Oa7mNeOBcEBAMBot+DoPVxPV/czMLb1mRXxcdDHPimbe4vn6NVM0W80I4lmLf0X7a2r0c7xku2K7XKbQsrqC1xcXaZdWYTforcJZCCCGEmE0keBZijogeP4b/2WdIdHWeW6koONZvJL1hI9/++bME//kLVFSU89//++ew2yvyuzmdzqKeo3Z1I2vvuxlbTWl+3eCBXpaGGvjnx34qVbPFnJZMZXjr5ABt7T4OnR4koxZOY1haX8qmFjc3rKqhtETm8wshhBDiHKm2PU1zqWqcmB+S/f0M/OxZwvv3jVuvX7GSnw8O8NOXduH19hKPn+utXFOT7a389a8/hsFgwOPp4c47b5s0dVvRKdzw8VtZ/N6mfOsdJQ33NL6HO1e9+1K9NHEVu1zvpaqqcaQ7QFuHl/3H/MSTmYJ9aitLaG1x09rsotppvWTnIuYW+bwXs51co2K2m0vXqFTbFmKOy0QjDP3nrwju2omWPlfptyeZ4Fvth3j9P39JJlMYCAD09/fzzDNPo2kKW7c+QX19A5s338X27U8XFA2z1TjY+JnNVK5w5QPnpWWL+MvmD1FprSg8uBCznKZpdPtCtLX72HPEx3A4WbBPmd3Exlzhr0aXXQp/CSGEEGJKEjwLMctoqsrwKy8x8MtfoIbD+fXDqRTbOg7z6+5OivntTtM0du3agcfTQ319Q26ussKuXTvw+/sBWHjLCq7/xC35FlQ6RccfLr6Tuxa+C50iRZHE3NIfjNHW7qWt3Yd3KFqw3WrWs25FDa0tLlY1lqPTScAshBBCiOJJ8CzELBI/043v3344bl6zYjDw7709PL73DWKZwl6zF+L397Nt2xM8+ugXMRgMbN36BB5PD09+73ECixJoC871ba6yVvJXzR9mcVnjjL0eIS61kWiSvUeyhb9O9Y4UbNfrFK5dWsmmFjfXLq3EZJTCX0IIIYS4OBI8CzELqPE4A7/8BcGdO2BMWrVjYyt9y5fzL/d+YNo9mkcFg4HxK8r0GP+gEi16bv5za+0NfHD5H2MxWC7qOYS4nBLJDAdO+Gnr8HH49BDqBP82VixwsqnFxQ2rarBZjBMcRQghhBBieiR4FuIKC791gP6nnyI9dK71lKmuDtfH/wrr8hV87I5bLjpwBnA6y4FsGvfrfW/w0+O/JKVmR7AtejMfWfWnrHNd985ehBCXWEZVae/MFv46cHyARKpwvn9DtY3WFjcbm1xUlskPQUIIIYSYWRI8C3GFpIaG8P/kx4QP7M+vU4xGKt73x1T8wXtRDNl/nqHQxVehr66uYcuWTxNPJ3jm2C/Y63szv22BvY6/Wf0xakqqLv5FCHEJaZrG6b4R2tp97D3iYySaKtinotTMxmYXm5rdNNTYr8BZCiGEEOJqIcGzEJeZpqoEX9zFwC9+hpY4116qpLmFmo/+BSaXa9z+DkdxpfPPpygKd9xxJ5Tp+eq+rfjGpGnfWr+JDyx7H0a9pLOK2cc7FM0X/uoPxgq2l5gNrG+qobXZxfIFTnRSKVsIIYQQl4EEz0JcRkmfD+8Pvkv81Mn8Or2jlOoPfQTHho0Ttsv56le/wd13b55W6rbL5eJd797MBz/7F3xt32PnpWn/Getca975ixFiBg2HE+zJFf7q8hZmWxj0Oq5bVklri5trllRiNEg1eCGEEEJcXhI8C3EZaJrG8Ksv49/+E7TkuZ6zZbfeTtWffhC9zTbpY9etW8+iRYvp7Dx9weewWq243bW85z3v5bP/8Ai/6N7JMyd+kd8uadpitonGU/z+7V5eP9RHR3eA838fUoBVC8tpbXGxbkUNJRb5yBJCCCHElSPfRIS4xNLBIL4f/YDIoYP5dcbqalx//beUrFhZ1DFeeaWN225rpaurs2AE2m638+EPf5wHHniQurp6AskA3z70b3QPe/L7SJq2mC3SGZXDp4fYc8THgRMDJCco/LXQ5aC1xcWGJhflDvMVOEshhBBCiEISPAtxCYX278X31I9Qw+H8usMGPYf1Oj5hs1FS5HEsFgt79rzF/v17+dznHiYcDuFwlPK1r32TtWvX5fdrHzzKD9t/QjSdnSdq1pv46Ko/k2ra4opSNY2TPcO0dWQLf0Xihf3Kq8ostLa4aG12U1c1eSaGEEIIIcSVIsGzEJdAJhql/yf/h9Du1/PrAskkX3xzH7v7vQA88/Pn2Lz5Lr7xjccwGIr7p7hu3Xp27fp9wXpVU3m+6yX+s3MHGtmRaVdJNfdd8xe4ba6C/YW4HDz+MG0dPtrafQyOxAu2O0pMbGiqYWOTi6X1pRPO+RdCCCGEmC0keBZihkWPHsH7g++O69v8cq+Hrx08wPCY+c4DA362b38aUNi69YmLfr5YOsa/dTzLwYH2/Lr19Wv46MoPYsR00ccV4mIMjcTZcyQbMJ/tDxdsNxl0rF1RzU3X1HLLugWERmKk0+oVOFMhhBBCiOmR4FmIGaKpKoO/+iVDv/4P8pWPzGb+9fBBnjvSPvFjNI1duxNq4NAAACAASURBVHbg8fRQX98w7efsi/j4zqEf0R8dAEBB4Y+XvYcPX/8+hoMSlIjLIxpPse+Yn7Z2L8fOBDm/LryiQMuiClpbXKxdXo3VbMBg0GHQS8VsIYQQQswdEjwLMQPSIyN4v7uN6Jgg2bqqiR8PDU4aOI/y+/vZtu0JHn30i9N6zjf7D/LUkWdJZrKj2SUGK3/d8hGudTWhUyQoEZdWKp3h4KlB2tp9vH1qgHSmsJXa4trSfOGvMptkQQghhBBibpPgWYh3KHbiBH3feYJ0IJBdoShUvf9PKX/P3fT+/QNFHSMYDBT9fKqm8qvTz7Oj+6X8unp7Lfdd8xdUWSunde5CTIeqaRw7E6St3cu+Y35iicLCX65yK60tblqbXbgqii2JJ4QQQggx+0nwLMRF0jSN4AvP4//ZTyGTbbejLyuj9r5PUbJyFQBOp7OoYzmd5UXtF08n+FHHM+PnN7vW8pFVf4pJLyN7YuZpmsbZ/jBt7T72HPERCCUK9im1ZQt/bWpxs8jtkMJfQgghhJiXJHgW4iJkolF8//v7hA/sz6+zrlxF7X33Yyg7FzBv2fIAzz33LAMD/kmPVV1dw5Ytn57yOQdjAbYd+iGecB+Qnd/8geXv410NN0uwImbcwHCMPblK2Z6BSMF2s0nP9cur2bTaRdPCcvQ6mSoghBBCiPlNgmchpil+ppu+J58g1e/Lrztst7Hh3g+PC5wB6usb2Lz5LrZvfxpNK5wTqigKd9xx55TFwk4Fu/jOoR8RTmWDGKvBwt+0fJTmypUz8IqEyArHUuw92k9bu5cTPcMF2/U6hdWLK2htcXPd8irMRv0VOEshhBBCiCtDgmchpmHk9dfwPfVDtFQKgFAyyT8d2MfrPi9VO343Yd/mb3zjMUBh164d+P39+fXV1TXcccedue2Ta+vbx0+O/oy0lk0Nr7ZWcv+1f43bVjPzL1BcdRKpDG+fHKCt3ceh04Nk1MIfeZY1lLHp/2fvvqPjKu/8j7+nqZdRnbEld7lIY2NjXGQ62KYTAqEmJJRAHIpJ1mRDcja7m83JCb9ks4QSQxQWCKEEEycEkgAxpmVDLDdcJVnuRWNrVEe9TLm/P8YesMdN0kgayZ/XOTno3ueZe5+xH+f44/vc71PkYNaUXFKT9HqAiIiInJkUnkVOgxEMUvfGH2h856/hc9u8jfz7utUcam8HTrxvs9Vq5cknn8btrqKkZCler5eMjEwWLbqfkSPzTnjPoBHkzV3vsHL/x+FzkzIKuGfq7STbVIhJei8YNKjY10hpWTXrt9fS2R2I6DMiK4l5Lidzixzk2BMHYZQiIiIisUXhWeQUgl1dVD/3a1o//ez95j/t3c0TWzfjCx69j/LJ9m3Oy8vnRz969LTu2env5IWy37G1viJ87oK8edw08QtYzFoqKz1nGAZ7q1soLfOwpsJDU1t3RB97ShxzixwUFzkZ7UjRu/QiIiIinxP18PzMM8/wyiuv0NrayowZM/jxj39Mfv7J3+cUiVV+byPup56ga99eAILA45s38se9u0/4md7u23xEQ2cjz2x6gYNt1QCYTWZumvgFLsw/t1fXkzNbTWM7pWUeVpV78DS0R7Qnxls4Z3Iu84ocTB6dgdmswCwiIiJyPFENz6+88gpvvfUWv/3tb8nNzeXxxx/nN7/5DT/4wQ+ieRuRAbF/3Vrqf/0MyUeeLsfH8xeMkwbnI3qyb/PnHWhx88ym52nqbgEg0ZrIPVNvZ0rmxF5dT85MzW3drKnwUFruYffB5oh2q8XEWROyKS5yML0gC5tVqxlERERETiWq4fn555/nkUceYfz48QAKzTIk+f1+fv7Nu7nSHyT5cOGvQ+1tPLpxPa0Jp/fu5+nu2/x5W+sqeK7sFboDoeW0OYlZ3Df9bhxJOT2+lpx5Orv9bNhRx6qyasr3NBI8TnX3yaPsFLtChb+SE2yDMEoRERGRoStq4dnj8VBVVUVTUxNXXXUV9fX1zJ07lx/+8IdkZmae1jXMZlPMLxm0WMxH/VeGF5/Px4+vu5JbnSMxHw7OWxvq+f7aUhq7ugCIj4+n6/DPx5Obm8v99z+I1Xr6c+TvVaX8ruKPBI3QU+4J9rHcP+MuUuKSe/wdNEfPHP5AkLI9DfxzSzXrt9fQ7QtG9BmVm8K5U50Uu5xkpScMwiiPT/NUYp3mqMQ6zVGJdcNxjpqM420+2wubNm3i5ptv5vzzz+cnP/kJhmHw0EMPkZ2dzdNPP33qCxAqaKMCNTJYgn4/v77pFqZ9Ln+8V3WARzeup/tzhcESEhLo6uo64b7Nd9xxBy+88MLp3dMI8tqWt/hTxd/C54rzZ/Lg3DuIs2pLIIlkGAaV+xr56NMq/rHJTVNrZOGvnIxELjo7n4tn5jNmRNogjFJERERk+Inak+cjQeKee+7B4XAAsHjxYu699166urqIj48/5TUaGtqGxJPntLREmps7CAQin/LI0BTs7mbnYz8/Kjg/t62cF7Zvi+jb2dnJlClTaGhooKbms32bc3ND+zb/7GeP09jYdsp7+oJ+Xty6jLXVG8LnFo65iBsmXU1bi482fL36Lpqjw9PBujb+ubWa0q3V1Hg7ItqTE6zMKXQwb6qTSaPtmA//Q+TpzMXBoHkqsU5zVGKd5qjEuqE0RzMyTm+1Z9TCc3Z2NgBpaZ895cjLy8MwDOrr6xk5cuQprxEMGgSDUXkQ3u8CgSB+f2xPAjk9wc4O3E89gb8yFJS7AwF+snE9K91VJ/zMjBnn8Mgj/3bCfZtPNTfafe38estv2eENFR8zYeLGSV/g4vzzCAYgSN/nlubo0Odt7WJNeahS9r7qloh2m9XM9IJs5hU5mDo+C9vhVwWCAYMg+v9SkWjQHJVYpzkqsW44zdGohWen00lKSgoVFRW4XC4A3G43NpuN3NzcaN1GJKoCLS1UPfEYXXv3ANDu9/HI6lVsqK876efs9owe7dv8efUdDTy96Xmq20NPrW1mG3e7vsxZOa6efwEZdjq6/KyvrKW0vJqKfY0c+3aAyQSFYzIoLnIyc1IOSQlR33FQRERERI4jan/rslqt3HjjjfzqV79i9uzZpKSksHTpUq699lqsVv3lTmLPgYpyDj3xGHa/H4BO4Fv//AcVp9hmKjExkUWL7u/VPd2th/jlxv+l+fBWVKm2FL45/U7Gpo3u1fVkePAHgmzZVc+qcg+bdtbhO86/zo5xpjKvyMGcIgf2lFO/BiMiIiIi0RXVVPvwww/T3d3NTTfdhM/n4/LLL9d2VRJz/H4/P/z2A1zubcKREKo+XNfZwQ/Lt7K7o/2Un1+48HLy8vJ7fN+d3j38avMLdPg7AXAk5XD/9K+TnXh61ehleAkaBjurmigtq2btthraOv0RfXLsCRQXOSl2ORiR1fPK6yIiIiISPVGrth0NtbWR7/TFGqvVTEZGMo2NbcNm7f6Z5r8eXMRl3iayDgdnd1sr/7LqHxxsP3VwHjduPJ98sq7Hqym21JXz3NaX8QVDAWls2mjum34XKbboByLN0dhWVdtKaZmH1eXV1DdHbnmWkmhjTmEuxS4nE0amDdsdCDRPJdZpjkqs0xyVWDeU5mhOTupp9dN6ajmj7C9dxTUtraQeDs67mptYsuoT6rs6w33i4xNISkqisbEhfC4hIZGFCy+npOT5Hgfn0kPreGXb8vAezoWZk7hn6ldJsGrp7ZmiobmT1eUeVpV5qKptjWiPs5mZOTGHYpeDorGZWIfRfogiIiIiw4XCs5wx2srLaHnu16TabACUNTTwndWf0OI7ekuorq5ObrrpFlJSUo5bSbsnVu7/mDd2/jV8PMsxg68W3ozVrD96w117p491lbWUllVTud8bUfvabDLhGpdJscvB2ROzSYjTnBARERGJZfrbmpwR2ivKOfjU49gOv6WwrraG769ZRUcgcNz+fr+/V5W0jzAMgz/tepuV+z8On7so/zxunHgtZpOeKg5XPn+ATTvrKS33sHlXHf5A5Fsx40emUVzkYE6hg7TkuEEYpYiIiIj0hsKzDFtudxUlJUtJrK/num4f1sPB+e+HDvLD9WvoDp743Qu7PaPX9w0EA7y67Q+UVq8Ln7tm3OVcMfbSYfv+6pksGDSo3N/IqnIP6ytr6eiKLPzlyExiXpGDuS4HjoykQRiliIiIiPSVwrMMO36/nyVLFrNy5QocgQC/mHceVmtoqfYODB7fs+ukwTknJ7fXW1F1B3w8X/YKW+rKATBh4pbJ13NBXnGvriexyTAM9ntaKS2vZk1FDY0tkYW/0pLjmFvooNjlYKwzVf9wIiIiIjLEKTzLsLNkyWKWLXuVSWnp/M+5F5B0ODiv8lTzb+tWkzd6DKb6Oo5XaN5kMjF//sJebUXV6e+iZMuLbG/cCYDVZOEO123MzD2rb19IYkadt4PScg+l5R4O1rVFtMfHWThnUqjwV+GYDCxmLdEXERERGS4UnmVYcburWLlyBRNS0/jFvPNJOVwcbG2th39bW0p3MEhrayvXXPNFSks/oba2JvzZnJxc5s9fyGOPPdXj+3b4O3h60/PsbtoHQLwljkXT7mRyZkF0vpgMmpb2btZtq2FVuYedVU0R7RaziWnjsyh2OZhekE28zTIIoxQRERGR/qbwLMNKSclSUrs6+cW5F5IWFyrGtKGulu+vKQ0v1a6trSEvL48VKz6ipGRpnytqt/raWLrxf9nf4gYg0ZrIA9PvZlz6mOh9MRlQXb4AG3fUUVpWzdY9DQSCkasUJuanU+xyMntKLimJtkEYpYiIiIgMJIVnGV4aGnh83gVkxIf2UN7SUM93V6+i85iq2l5vI3l5+X2qqA3Q3N3CUxue5WBbNQAptmQenHEPo1J7HsJlcAWCQSr2NVJa5mH99lq6uiMrsY/MTqa4yEFxkYNse+IgjFJEREREBovCswwb3TU13NDtIykhAYCKxka+U/oJHYHI6sd9qaZ9RGOnlyc3/pqa9joA0uJSeejsbzAi2dHna8vAMAyDvdUtrCoLFf5qbuuO6JORGh8u/DUqN0WFv0RERETOUArPMiz46uup+vlPSTq8NHt7k5clpf+gzR8ZnPtSTfuIuo4Gntzwa+o7GwDIiLfz0Nn3kpuU06frysDwNLZTWuahtKwaT2NHRHtivJVZk3ModjmZPMqO2azALCIiInKmU3iWIS/Q1ob7if/B31APQL3JxJLST2jx+SL69qWa9hGethqe3Pgs3q5Q8ajsxCwemvENshL7/jRb+k9zWzdrKjysKvOw51BzRLvVYmL6hGyKXQ7OmpCFzarCXyIiIiLyGYVnGdKCPh8Hlz5J98GDANgcDs5++LtckZjI+++viFo17SPcrYd4asOztPhaAXAm5bL47Huxx6f37YtIv+js9rNhex2ryqsp39NI8JjtyUzA5NF2il1OZk3OISlBhb9ERERE5PgUnmXIMoJBPM8/S8f2SgAsqWnkffth4jKzePLJp3G7q6JSTfsId+shntzwa1p9of1981JGsHjGvaTGpUTl+0h0+ANByvY0UFruYcOOWrp9wYg+o3JTKHY5mFvoIDMtYRBGKSIiIiJDjcKzDFl1y1+nZe0aAExxceQ99G3icnLD7dGopn3EscF5TNooHpz+dZJsSVG5vvSNYRjsOtjMqrJq1lbU0NoRuWQ/Ky2BYleoUnZejv7BQ0RERER6RuFZhqTGlStoXPFu6MBkYsQ37ydh3Ph+udexwXls2mgenPF1Eq3aqmiwHapvY1WZh9Xl1dR6OyPakxOszC4MBeaC/HTMqpQtIiIiIr2k8CxDTsv6tdQu+134OPf2O0g5a0a/3Otga7WCc4xpbOliTYWH0jIP+zwtEe02q5kZBaHCX9PGZ2G1mAdhlCIiIiIy3Cg8y5DSsWMH1c+WwOHCT5nXXIv9oov75V4HW6t5YkPJ0Uu1FZwHRUeXn3WVNZSWedi2rxHjmHaTCYrGZFDscjJzUg6J8fq/NhERERGJLv0NU4aM7kMHcf/ycYzDezennXseWdfd0C/3igjOqaN4cPo9Cs4DyOcPsmV3PaVl1WzcWY8/EFn4a6wzlWKXkzmFudhT4gdhlCIiIiJyplB4liHB3+Sl6onHCLaFwmxSkQvH1+7C1A/vsB43OM+4hySbgnN/CxoGOw54WVXmYX1lDW2d/og+OfYEioucFLscjMhKHoRRioiIiMiZSOFZYs7nt5iy2+184657Cbz8W/x1dQDEjxrNiPsexGSN/vQ91OY56h3n0an5Cs4DoKqmlVXl1awu99DQ3BXRnppkY84UB8UuB+NHpvXLP5qIiIiIiJyMwrPEDL/fz5Ili1m5cgV1dbXh8/mbNnHx4S2orJlZ5H3rX7AkRj/MVrfV8MSnJbT4WoFQcF6s4NxvGpo7KS33UFpWTVVtW0R7nM3MzEk5FBc5KRqbocJfIiIiIjKoFJ4lZixZsphly17FMD4rB3XL+IJwcO4GxnzrX7DaM6J+77qOep7c8OvPBee8w8FZ+zhHU1unj3XbQoW/Kg94I9rNJhOucZnMczk4e2IO8XGWQRiliIiIiEgkhWeJCW53FStXrjgqOM/KzuF+17Tw8S8qK/gRkBflezd2enlyw7M0dTcDMCplJItn3KvgHCU+f4BNO+tZVVbNlt31+APH1sqGCSPTKHY5mT0ll7TkuEEYpYiIiIjIySk8S0woKVl61FLtkUlJ/NesOVgOv9v6m8pt/LmygrySp/nRj34Stfu2dLfy1MZnqe9sAMCZ7OBBBec+CwYNtu1vpLTMw/rtNXR0BSL6ODOTKHY5KC5ykJuhX28RERERiW0KzxITvN7PlvAmWCz8ZM480uNCWw99Un2I5yrLD/drjNo923ztPLXxWTztodCenZjF4hn3kBKnCs69YRgG+z2tlB4u/OVt7Y7ok54cx9yiUOGvMY5UFf4SERERkSFD4Vligt1uD//8/RnnUJCWDsC+lhZ+9OlajHC/6Lzv3OnvZOmm53C3HgIgI97OQzO+gT0+PSrXP5PUejvChb8O1bdHtCfEWThnUg7FU50Ujs7AbFZgFhEREZGhR+FZYsKiRQ+wfPnrXG7PYH5ePgBtPh/fX7uKNn9or9+cnFwWLbq/z/fqDnTzzOYX2Nd8AIDUuBQWn30vWYnRL0Q2XLW0d7P2cOGvne6miHaL2cS08VkUuxzMKMgmzqbCXyIiIiIytCk8S0zIy8vn7kvmc03nZ3v8/ujTtexvDVW/NplMzJ+/kLzDwbq3fEE/z255iZ3ePQAkW5NYPONeHEk5fbrumaDLF2DDjlpKyzyU7WkgEIws/DUpP51il5NZU3JJSbQNwihFRERERPqHwrPEhG5PNV+0WAmaQu/JPrutnE881UDoifP8+Qt57LGn+nSPQDDAC2WvUt5QCUCCJZ4HZnydvJQRfRv8MBYIBqnY28iqsmo+3V5Hly+y8FdedjLFLgdzixxkp2tPbBEREREZnhSeZUC53VWUlCzF6/Vit9tZtOgBRmRlcXDpkwTbQ+/LWgqLSBzh5NaZ55CRkcmiRfczcmTfNqgKGkFeqvg9m2q3AmAz27hv+t2MSRvV5+803BiGwZ5DLZSWVbOmwkNzuy+iT0ZqfKjwV5GDUbkpKvwlIiIiIsOewrMMCL/fz5Ili1m5csVRW1ItX/46P7vgYiYFQk8040aOZPQDi/lRQvSeYBqGwR93/IW1nk8BsJosLDrrDgrs46J2j+HA09DOqrJqSss91DR2RLQnxVuZNSWH4iInk0bbMSswi4iIiMgZROFZBsSSJYtZtuxVDOPo92TnJiWFg7M5MZGRDzyEOYrBGWDFvg/5sOofAJgwcffUr1CYOSmq9xiqmtq6WVPuobS8mj2HWiLarRYz0ydkUexyctaELGxW8yCMUkRERERk8Ck8S79zu6tYuXJFRHAem5LKv0ydHj62XXsdcQ5nVO/9ycHVvLX73fDxl6fcyPScqVG9x1DT0eUPF/4q39tI8JjfFxMwebQ9VPhrcg5JCSr8JSIiIiKi8Cz9rqRk6VFLtQHizGZ+OGsOCdbQFHxj727a/vF3fnTZFVG776barfxu2x/Dx9dNuJJzR86O2vWHEn8gyNY9DZSWVbNxRx3d/mBEn9G5KRS7nMwpzCUzLWEQRikiIiIiErsUnqXfeb3eiHOLXWdRkJYOwK7mJp7aupkbilxRu+eOxl08X/YqBqGnqpeOuoCFoy+O2vWHAsMw2FHlpbTMw9ptNbR2RBb+yk5PCBX+cjnJy04ehFGKiIiIiAwNCs/S7+x2+1HHF40YyfXjxgPQ6ffzw/Vr6A4GsdszonK/Ay0H+dXmF/EH/QDMdszk+oKrz5iK0O7aVv68ah8frjtAXVNnRHtygpXZhQ7muRwU5KWfMb8uIiIiIiJ9ofAs/W7RogdYvvx16upqcSYm8b0ZM8Ntj2/dzJ6WFnJyclm06P4+36u2vZ6lm/6XzkAoNBZlTearhTdhNg3vQleNLV2sPlz4a7+nNaLdZjVz9sRsioucTB2fidUyvH89RERERESiTeFZ+l1eXj4LFlzG8td/x3+eM5tUWxwAK90H+Mv+vZhMJubPX0heXn6f7tPU1cIvNz5LS3coPI5LG8M9U7+KxWzp83eIRe2dftZX1lBa7mHbvkaMY9pNJigam0lxkYOZk3JIjNcfdxERERGR3tLfpmVAPPbYUxR3+5jmDy2lPtjWxn9v2kBOTi7z5y/kscee6tP1O/wdPL3pOeo6GwBwJju4b/pdxFvi+jz2WOLzB9m8q57S8mo27azHH4gs/DVuRBoL5oxm2rgMUlQpW0REREQkKhSeZUB0ba9k1uH9nIPAJ5mZfO3e+1i06H5Gjszr07X9QT/PbnmJqtaDAGTE23lw+tdJtiX1ddgxIWgY7DjgZVWZh3Xbamjv8kf0ybUnUuwKFf7Kz00hIyOZxsY2/Mepqi0iIiIiIj2n8Cz9zt/URPVzv4bD+wnn3ngz/3bFVVG5tmEYvLrtD1Q27gQg2ZrEgzPuISPBfopPxr4DNa2UllWzusJDQ3NXRHtako3ZhQ6KXQ7Gj0hT4S8RERERkX6k8Cz9yggGqX7+WQJNTQAkuaaSEcW9nP+65z1WV68HwGq28s3pd+JMzo3a9QdafVMnqys8rCqrxl3bFtEeb7Mwc1I2xS4nRWMzsJhV+EtEREREZCAoPEu/avr4I9rLtgJgSUvDefe9mKIU+P55cC3v7F0JgAkTdxbdxvj0sVG59kBq7fCxrrKG0jIP2w9E7oltNpmYOj6TYpeDswtyiI8bngXQRERERERimcKz9BtfbS21y5eFj51334s1PT0q1y6vr+R3lX8IH99QcDVn506LyrUHgs8fYNPOelaVVbN5Vz2B4LG1smFCXhrFRU5mF+aSljS8Cp+JiIiIiAw1Cs/SL4xgkOrfPIfRFXpXN/3Ci0meGp1we6DlIP+79SWCRqgY1iX553Pp6Aujcu3+FAwabNvfSGmZh/Xba+joCkT0GZGVRHGRg7kuJ7n2xEEYpYiIiIiIHI/Cs/QL70cf0FG5DQBrVhY5N98Sles2dnp5ZtPzdAW6AZieM5UbJl4TlWv3B8Mw2O9pZVVZNWsqPHhbuyP6pKfEMbfQwTyXk9GOFBX+EhERERGJQQrPEnXdNTXULX89fOy88+uYE/r+FLXd18HSTc/R1N0MwLi00dxZdCtmU+wVzar1dlBa7qG0rJpD9e0R7QlxFs6ZnEOxy0nh6AzMZgVmEREREZFYpvAsUWUEg3he+F+M7tAT1vSLLyWpsKjP1/UH/Ty79SUOtXkAyE7MYtFZdxJniZ13gVvau1m7LVT4a6e7KaLdYjZx1oQsil1Opk/IIs6mwl8iIiIiIkOFwrNElfeDlXTs2A6ANTubnBtv7vM1j+zlvP3IXs62JB6YfjepcSl9vnZfdfkCbNhRS2mZh7I9Dcct/DVplJ1il4NZk3NJSbQNwihFRERERKSvFJ4laro91dT9cXn4OLRcO6HP1/3bvg/DeznbzFa+edZd5Cbl9Pm6vRUIBqnY28iqsmo+3V5Hly+y8FdeTnKo8FeRg+x0Ff4SERERERnqFJ4lKoxgkOoXngsv17ZfOp+kKYV9vu6Gmi38efe74eM7im5jfPqYPl+3pwzDYM+hFkrLqlmzrYbmtsjCXxmp8RQXOSh2ORmVO/hPxUVEREREJHoUniUqvCvfo3PnDgBsOTlkf6nvy7X3N1fxYvlr4eMvjL9iwPdy9jS0s6qsmtXlHjyNHRHtSfFWZk3JZZ7LwcRRdsyqlC0iIiIiMiwpPEufdVcfou6Nz5ZrO+66B3N8fJ+u6e1q4lebf4Mv6ANgjnMml425pE/XPF1Nbd2sKfdQWl7NnkMtEe1Wi5kZBaHCX9PGZ2Gzxl61bxERERERiS6FZ+mT8HJtXyjk2hcsJGnS5D5dszvQTcnm34S3pBqfPoYvT7mxX/c/7ujyhwt/le9tJGgcXfjLBEwZk0FxkYNzJueSlKA/OiIiIiIiZxIlADklt7uKkpKleL1e7HY7ixY9QF5ePgCN7/2Nzl2hKti2XAfZ19/Yp3sFjSAvli9jf4sbgKyEDL4x7Q5s5uhPVX8gyNY9DZSWVbNxRx3d/mBEn9GOFIqLnMwtcpCR2ren6SIiIiIiMnQpPMsJ+f1+lixZzMqVK6irqw2fX778dRYsuIyf/eCH1L/5RuikyYQzCsu1/7p7BRtrtwCQYInnm2fdFdUtqQzDYKe7idIyD2u31dDa4Yvok5WWQLErVPgrLzs5avcWEREREZGhS+FZTmjJksUsW/YqxjFLmOvqalm27FWu7OpmQiC0TVP6xZeSOHFin+63pvpT3t33AQAmTNzl+jIjU5x9uuYR7ro2Sg8X/qpr6oxoT0m0MXtKLsUuBwV56f26RFxERERERIYehWc5Lre7infffTsiOB8xL9cRDs6WtDSyr7+hT/fb3bSXVyp+Hz6+YeI1TM3u21ZX4ecH6wAAIABJREFUjS1drD5c+Gu/pzWiPc5qZsbEbIpdTqaOy8RqUeEvERERERE5PoVnieD3+7n11hvwehuP2x5vsfDtqdPDxzm33IYlqffLm+s7GijZ/CJ+IxTGzxs5l0vyz+/Vtdo7/ayvrKG03MO2fY0cG/1NJigam0lxkYOZk3JIjNcfAREREREROTUlB4mwZMliKiu3nbD9jolTGJkcCssHzGYmzinu9b26At2UbHmRVl8bAJMyCrhl0hd7tGza5w+yeVc9peXVbNpZjz8QWfhr3IhUiouczCnMJT1Fhb9ERERERKRnFJ7lKG53FStXrjhh+5iUVG4rCL3b3B0IsCE3l/m9fD/YMAxeqfg97tZDAOQkZnHP1NuxmC2n/GzQMNhxwMuqMg/rttXQ3uWP6JNrTwwX/nJmJvVqjCIiIiIiIqDwLMf4+c9/elRl7WM9fNYMbObQu8F/OuTmrh8/2ut7vbf/I9bXbAIg3hLHorPuJNl28pB7oKY1VPirwkNDc1dEe2qSjTmFDopdDsaPSFPhLxERERERiYp+C88/+clPePHFF6msrOyvW0gUHdmW6o03lp+wz+X5o5iZnQOAu62V+omTwvs991RZfSVv7Xo3fHxH0W2MSHYct299Uyel5dWUlntw17ZFtMfbLMycFCr8VTQ2A4tZhb9ERERERCS6+iU8V1RU8Oabb/bHpaWfnGhbqiNSbTYedE0LH7/e0MBTL73Wq3vVtNfyQtmrGIfLeV01biHTc1xH9Wnt8LGusobSrdVsr2qKuIbZZGLq+EyKXQ7OLsghPu7US71FRERERER6K+rhORgM8p//+Z/ceeedPP7449G+vPSDI+85nyg4A3yj0EVGfAIAn9TV8oPnf4vV2vPp0+nvpGTLb+nwdwAwPdvFlWPnA9DtC7BpVz2lZdVs3lVPIBg5ngl5aRQXOZldmEtaUlyP7y8iIiIiItIbUQ/Pr732GvHx8Vx77bUKz0NEScnSk77nXGjP4Lox4wBo9/vYnj+Ku3qxXDtoBPlt+TKq2zwAOJMd3D7lFir2eSktq2Z9ZS2d3YGIz43ISqK4yMFcl5Nce2KP7ysiIiIiItJXUQ3PdXV1PPXUU7z00ku9+rzZbMJsju0CTxaL+aj/DgdNTd4TtllMJr5z1tmYDxfe+jQpkUd/+TRWa8+//593rWRTXRkACeYERrVdzA9+vQ5va3dEX3tKHMUuJ+dOdTLGmarCXz0wHOeoDD+apxLrNEcl1mmOSqwbjnM0quH50Ucf5YYbbqCgoICqqqoefz4zM3nIhKS0tOHzBNTpzD1h2/VjxzPZbgegwWrhu6+9isnS8/eL17o38Zddh7fAMqCpwsXfm45+lzkx3sp5Z43k4pn5TC3IxhLj/5AS64bTHJXhS/NUYp3mqMQ6zVGJdcNpjkYtPK9atYoNGzbwl7/8pdfXaGhoGxJPntPSEmlu7iAQCA72cKLirrsW8fLLr1BbW3PU+cz4eO6dUhQ+zr/7HrzNnT26dnNbNyu3lrOi8TU4/I9OvqpJBJtCVbstZhPTC7I5d6qTGROzibOFgnlzU3sfvtGZbTjOURl+NE8l1mmOSqzTHJVYN5TmaEZG8mn1i1p4fuutt6ivr+eSSy4BCBefmjt3Lv/xH//B1VdffcprBIMGweMUiYpFgUAQvz+2J8GpuN1VlJQsxev1kpmZSV1d7VFFw+6ZUkSyzQZAmcXC9XPmndZ37uoOsGFHLaXlHsr2e7AW/hNzgh8Af70T/6FxTBplp9jlYNbkXFISbeHPDvVf01gyHOaoDH+apxLrNEcl1mmOSqwbTnM0auH5e9/7Ht/61rfCx9XV1dxyyy28+eabpKenR+s2EgVH9nReuXLFUYXC4uPjARNdXZ0UpKVzzeixAHQBV/2/n5/0moFgkPK9jawqq2bD9jq6fAHAIK5gM+aE0FNkS1c6l+d/gfMuyycrPaF/vpyIiIiIiEg/iFp4Tk9PPyok+/2hJ41OpzNat5AoOdGezl1dXQBMmjSF/yqaijkY+heivBtvJj4jI+I6hmGw+1AzpWUe1lZ4aG73HdVude7BkhlaCp5gSeD7F99HdmJmf3wlERERERGRfhX1raqOyM/Pp7Kysr8uL710Ons6jzcMRh0OzrbsHOzzFxzVXt3QTmlZNaVlHmq8HRGfT4q3MqkwwPa4HRy5y12u2xScRURERERkyOq38Cyx6VR7OltMJm7PHxU+zr7xJsy2OJpau1hdUUNpWTV7q1siPme1mJlRkEWxy8moPCv/8+lTGL5QdL5y7HymZhdG/8uIiIiIiIgMEIXnM4zXe+I9nQGuGzOOsalpAMSNn8DmuHxKl22kfG8Dxz6sNgFTxmRQXOTgnMm5JCVY8Qf9PLGhhBZfKwCFmZO4atzC/vgqIiIiIiIiA0bh+QxjOckezSlWG3dP+ewJ8W8CU9j/9raIfqMdKRQXOZlb5CAjNf6otj/tfJvdTfsAyIi3c2fRbZhNw2djdBEREREROTMpPJ8hjlTYfu+9d4/TaiJj5BQWnzUTe1zoHeaylHHst2WFe2SnJ1DsclBc5GRk9vH3QVvv2ciHVf8AwGqycO+0r5ISd3p7pomIiIiIiMQyheczxPEqbKdk5pNXeBF5Uy5kZFISl+57EwCfycLHWWeTkmhjdmEu84qcTMhLw2QynfD6h9o8vLxtefj4xklfYEzaqBP2FxERERERGUoUns8An6+wnZCSycjJF5BXeBHpuePDfS4+9DFWQhW2qybM4q4bz8U1LhOr5dRLrjv9nTy75SW6A90AzHHO5PyRxf3zZURERERERAaBwvMZ4JmSEhKd0ym++EKyRk3FdMw7yHnth5jSFnpP2ZyaysJv34k5IfG0rm0YBi9vW46nPbSf88hkJ7dNvuGkT6lFRERERESGGoXnYcrnD7J5Vx2lZR4OJl7I9MsuiejTeGg7B7d9zBfTOiE9HYDs67902sEZ4KOqT9hQsxmABEsC9077KnGWuOh8CRERERERkRih8DyMBA2Dyv1eSsuqWVdZS0eXP9Rg+qzCdlvjQaoqPubgtr/T5j3EwrxRTBk1G4BGq5WJ51942vfb13yAN3b+NXz8taKbyU3Kic6XERERERERiSEKz0OcYRgcqGmltMzD6goPjS1dEX2SEyzs3PA3dm34G97qHeHz8RYL3yxyhY9HfPl2TObT21aq3dfBc1tfJmAEAJg/+kKm50zt47cRERERERGJTQrPQ1RdUweryz2Ulnlw17VFtMfHWZg5MYeJTgvv//lFGra9jbd691F9bhlfgCMxCYC9ZjOXXXjxad3bMAxe2fZ76jsbARiXNprrxl/Zty8kIiIiIiISwxSeh5DWDh9rt9VQWlbNjqqmiHaL2cTUcZkUu5xMHWfn+498m1+sXEFdXW24j8lkwjAMUm02vlwwCYAgcP4Pfnja4/jY/U821m4FIMmayF2ur2AxW07xKRERERERkaFL4TnGdfsCbNwZKvy1ZXc9gaAR0acgP515RQ5mTcklNSlUrOuhh+6L2NcZCB/fd84cUmw2AOwXXEjS6NGnNZ79LVW8seMv4ePbC28mKzGjV99NRERERERkqFB4jkHBoEHF/kZKt1azfnstnd2BiD4jspIodjkpLnKQYz+6OrbbXcW7774dEZyPsMfFc1lWNgAmq5Wsa647rXF1+Dt5busr+A+/53zJqPOZnuM6xadERERERESGPoXnGGEYBvs8LaHCX+Uemtq6I/rYU+KYW+SguMjJaEfKcfdS9vv93HrrDXi9jSe81+0TJ5FgCS2zTr/wYmxZWac1vt9t+wN1HfUAjE7N54sTrjrdryciIiIiIjKkKTwPsprGdkoPF/6qbmiPaE+Mt3DO5FzmFTmYPDoDszkyMH/ekiWLqazcdsL2nIRErh87HgAfkHn1Nac1zn8cXM36mk1AaD/nr0/9Clazpo+IiIiIiJwZlH4GQXNbd7jw166DzRHtVouJaeOzmOdyMr0gC5v19Ipxud1VrFy54qR9vjZpMvGHnzpvT0nBlW4/5XWrWg6yfMdb4ePbC28iO/HUT6tFRERERESGC4XnAdLVHeDTHbWUlnko29NA8DjvI08eZafYFSr8lZxg6/E9SkqWHlVZ+1gjkpK4dvRYANr9fmY/8NApr9np7+S5spfxB/0AXJh3LmfnTuvx2ERERERERIYyhed+5A8EKd/bQGmZh0931NLtC0b0yc9JYZ7LwdwiB5lpCX26n9frPWn7nZMKsZrNAGxNSOD2iZNO2t8wDF6r/BM17XUAjEoZyQ0FV/dpjCIiIiIiIkORwnOUGYbB7oPNlJZ5WLPNQ0u7L6JPVlo8c4ucFLsc5OekRO3edvuJl2CPTknhilGh7ahaAwFueuzJU15vTfWnrPV8CkCCJZ67p96OzdLzJ+IiIiIiIiJDncJzlByqbwtXyq7xdkS0JydYmT0ll2KXk4L8dMzHqZTdV4sWPcDy5a8fd+n23ZMLsRy+Z8ZlVxCflnbSa9W017Fs+xvh49umfIncpOzoDlhERERERGSIUHjuA29rF2vKPawq97CvuiWi3WY1M70gm3lFDqaOz8JmNffrePLy8lmw4DKWLXv1qD2eJ6SlsSBvFADtwFk33HjS6wSCAX5T9ju6AqHtsopHzGKWY0a/jVtERERERCTWKTz3ULc/wPtr97Ny9T7K9jZwbN0vEzBlTEao8NfkXBLjB/aX+LHHngJMvP/+CmprawD4+uSicPuom27BHB9/0mv8dc977Gs5AEBOYhY3Tbyu38YrIiIiIiIyFCg899Djr29i6+6GiPNjHKkUuxzMKXSQkXrycNqfrFYrTz75NG53FSUlS4mrb+DCrq5QW0YGGZfOP+nntzfuYsW+DwEwm8zc5foyCdbB+z4iIiIiIiKxQOG5h2oaPnufOTs9gWKXk3kuByOykgdxVJHy8vL50Y8epeoXP6e9bCsAmVdfi9kWd8LPtPnaebH8NQxCj9OvHX85Y9JGDch4RUREREREYpnCcw99+5bp7K5uZURGAmMdqZj6ofBXtLRvrwwHZ1t2DunnX3jCvoZh8Oq25Xi7mgCYlFHAgtEXDcg4RUREREREYp3Ccw/l56QwbZKDxsY2/P7IfZtjhWEY1L/xh/Bx5rXXYbKe+Lf7n4fWsLE2FLSTrUncUXQLZlP/FjgTEREREREZKpSOhqmObRV07NgOgM3pJK143gn7etpqWL79rfDxlwtvxB6f3u9jFBERERERGSoUnoep+r/+Ofxz1he+iMliOW4/X9DPC2Wv0h30AXD+yLnMyJk6IGMUEREREREZKhSeh6GO3bvo2FYBgM3hIHXWnBP2/fPudznQehAAR1IuX5p47YCMUUREREREZChReB6GGt7+S/jnzCuuwmQ+/m9zRcN23t//dwCsJgt3uW4jznLiatwiIiIiIiJnKoXnYabLXUXbxg1AaF/ntHnnHbdfm6+dl8pfDx9fN+FKRqXmDcgYRUREREREhhqF52Gm4e2/hn/OuOyKE1bYXlb5Bk3dzQBMyZjIxaPOH5DxiYiIiIiIDEUKz8NId20NLWtXA2BOSSH9wouP22+dZyPrazYBkGRN5KtFN2tbKhERERERkZNQYhpGGt99B4Khvacz5i/EHB8f0cfb1cRrlW+Ej2+ZfL22pRIRERERETkFhedhwu/10vzJ/wFgik/AfumCiD6GYfByxe/p8HcAcE7udGY5ZgzoOEVERERERIYihedhovG9v2H4/QDYL74ES3JyRJ+/u1dR0bAdgPS4NG6ZfP2AjlFERERERGSoUngeBgJtbXg/+hAAk9VKxsLLI/p42mp4Y+dnxcS+WngzybakARujiIiIiIjIUHb8UswSk9zuKkpKluL1erHb7Sxa9AB5efl4P1iJ0dUJQNp5F2C124/6XCAY4MWKZfiCPgAuzDuXwqxJAz5+ERERERGRoUrheQjw+/0sWbKYlStXUFdXGz6/fPnrXDF/IfebD/82ms1kXHFlxOf/tu8D9jUfACA3KZvrC64akHGLiIiIiIgMF1q2PQQsWbKYZctePSo4A9TV1dK9dg3BtlYAUmfPJS4n96g++5oP8M7e9wEwm8zcUXQrcZa4gRm4iIiIiIjIMKHwHOPc7ipWrlyBYRgRbTazmVsnTAwfZ1519VHt3QEfL5YvI2iEtq+6fMyljE0b3b8DFhERERERGYYUnmNcScnSiCfOR1yWP4rcxEQADiQkEJ+Xf1T7W7vewdNeA8Do1DyuHDu/fwcrIiIiIiIyTCk8xziv13vc82bg9oLJ4ePSY55Mb2/cyYdV/wDAZrZyR9GtWMyWfhuniIiIiIjIcKbwHOPsx1TOPuLikXmMSkkBYF1tDV1ZWeG2Tn8XL1f8Pnx83YSrcCY7+negIiIiIiIiw5jCc4xbtOgBsrNzIs5/5XNPnf9c62HRovvDx2/uepv6zkYAJtrHc1H+uf0/UBERERERkWFM4TnG5eXls2DBZZhMpvC56ZlZTD78RHqbt5Gcc2aTd/h95+2NO/m7exUAcWYbX5lyE2aTfptFRERERET6Qvs8DwGPPfYUYOL991dQW1vDzRMKwm37c3N57Be/BI6/XDsnKevYy4mIiIiIiEgPKTwPAVarlSeffBq3u4pXlj7BhTWh6tum1FQe+O9fYLKGfhuPXa59Yf68QRuziIiIiIjIcKL1vENIXl4+d06fyZEF3JkLLgsHZy3XFhERERER6T9KV0NIoKOD5v/7GACTzYb9wosBLdcWERERERHpbwrPQ0jzJ/8g2NkJQNq8c7GkpgJHL9cusI/Tcm0REREREZEoU3geIoxgEO/774WP7fMvAyKXa98+5WYt1xYREREREYkypawhom3zJny1NQAkFbmIz8vTcm0REREREZEBovA8RDSuXBH+2b4g9NRZy7VFREREREQGhsLzENB1YD8d2yoAsDmcJE+dpuXaIiIiIiIiA0hpawhoXPnZu84ZCxbSbfh5uWJ5+JyWa4uIiIiIiPQvhecY529upmV16AmzOSmJtHnn8dfdK6jvbABgQrqWa4uIiIiIiPQ3hecY1/Txhxh+PwDpF1zEge5aPjjwfwBYzVa+UnijlmuLiIiIiIj0M6WuGBb0+fB++H7owGwm9eJLeGXbcgwMAK4auwBHUs4gjlBEREREROTMoPAcw1rXriHQ3AxAysxz+KhtK+7WQwDkpYxgweiLBnN4IiIiIiIiZwyF5xhlGMZR21MZ58/mnb0rATBh4itTbsRitgzW8ERERERERM4oCs8xqmPHdrr27wMgfuw4lnWuwx8Mvft86egLGJM2ajCHJyIiIiIickZReI5R3vc+e+pcc854djXvBSA7IZNrxl02SKMSERERERE5M0U1PLvdbh544AHmzp3Lueeey/e+9z2aD7+zK6fPV1tL68ZPATCnp/N6/PZw221TvkScJW6whiYiIiIiInJGimp4/uY3v0laWhoffPABf/zjH9mxYwc//elPo3mLM4L34w/BCFXU3lGUSTtdAMwbMZspmRMHc2giIiIiIiJnpKiF5+bmZqZOncrDDz9McnIyTqeT66+/nnXr1kXrFmeEoM9H8yehfZwNi5n3R7QAkBqXwg0FVw/m0ERERERERM5Y1mhdKC0tjUcfffSoc4cOHSI3Nzdatxh21q9fy3e/u4SWlhZSU1P52c8eY2IgQKAlFJj3jEqkIyH07xs3T/oiSbakwRyuiIiIiIjIGStq4flYW7Zs4eWXX+aZZ5457c+YzSbMZlN/DSkqLBbzUf/tjc7OTs47bw579+7BOLw8G+CqqxZQcskCilJSAfh0gg2AGblTmT1iOiZTbP/aSGyIxhwV6W+apxLrNEcl1mmOSqwbjnO0X8Lz+vXrue+++3j44Yc599xzT/tzmZnJQyYgpqUl9vqzBQXT2bNnd8T5UcnJ4eDckGbBnWsj0ZbAN+d+hcyklF7fT85MfZmjIgNF81RineaoxDrNUYl1w2mORj08f/DBB/zrv/4r//7v/84Xv/jFHn22oaFtSDx5TktLpLm5g0Ag2OPPr1u3lt27I4MzwBfGjAv/vHVCIphM3FBwNaYuG41dbb0es5xZ+jpHRQaC5qnEOs1RiXWaoxLrhtIczchIPq1+UQ3Pn376KY888ghPPPEE559/fo8/HwwaBIPGqTvGgEAgiN/f80nw8MPfPmqp9hFxZjNXjhoNgN8MFeMTGJ8+lmLn7F7dR6S3c1RkIGmeSqzTHJVYpzkqsW44zdGoLUD3+/384Ac/4Dvf+U6vgvOZYvfuXcc9f/HIPNLj4gHYMTqedivcNvkGzKbh846AiIiIiIjIUBW1ZLZx40Z27drFj3/8Y6ZNm3bU/9xud7RuM6S53VV0dnYct+2Ln1+yXZBI4+pDjExxDtTQRERERERE5CSitmx71qxZVFZWRutyw1JJyVICgUDE+XGpqZyVlQ1AXbqFHUYH/3LFgwM9PBERERERETkBrQkeQF6v97jnry8oCP+8tSCRitfWM3fWvIEaloiIiIiIiJyCwvMAstvtEefiLRauGD0GAJ8FVtYdYr7r0oEemoiIiIiIiJyEwvMAWrToAbKzc446d91MF0lG6LdhW14cO96p5IEHHhqM4YmIiIiIiMgJKDwPoLy8fBYsuAyTKbSXtcli5oZJny3Z/tOunVww6wLy8vIHa4giIiIiIiJyHArPA8jtriItLY2xY8eRmJjI/Ktnkd8SaqtOBnvaJB577KnBHaSIiIiIiIhEiFq1bTkxv9/PkiWLWblyBXV1tQAk5aRy/bgJsKcLAPsFl/DUjXcM5jBFRERERETkBBSeB8CSJYtZtuxVDMMInyv+2vkU7ukGoNsMrqtvHqzhiYiIiIiIyClo2XY/c7ureO+9vx0VnPPmjOOijFzi/KFzH9d4qG6oH6whioiIiIiIyCkoPPezkpKl1NfXhY+tCTZmfO1cpu3oCJ97rayMkpKnB2N4IiIiIiIichoUnvuZ2+0+6rjwhnMYZ0ogt9EPQEVjI5VNXtzuqsEYnoiIiIiIiJwGhed+tnfv7vDPqSPtTLpqGlN3fvbU+c19ewDYt2/vQA9NRERERERETpPCcz/zer3hn8+++3ziDROT9oUqbLf5fLzvPgDA2LHjBmV8IiIiIiIicmoKz/1o37694eXY+cUTcEzNp+BAV7hQ2Ep3FR2BAAAjR+YN2jhFRERERETk5BSe+9GXv3wTwWAQS7yV6V+dB0Dh7s5w+9sH9gGQmJjIokX3D8oYRURERERE5NQUnvuJ213Frl07ACj60jkkZaWQ2hpgVI0PgP2tLZQ1NgDgdI4gLy9/0MYqIiIiIiIiJ6fw3E9+/vP/RzAYPFwk7CwApuxsD7e/c2B/+OeFC68Y8PGJiIiIiIjI6VN47idr164B4Oy7zsdstYBhMLG8GYCgYfC3w+HZbLZw330PDto4RURERERE5NQUnvuJyQT5c8fjmBZajp25vYkcbACsr6uhpjO0XVVKSoqWbIuIiIiIiMQ462APYLg6Z+5cmuYGwscj/34QkrMBeHv/Z0u2r7nmCwM+NhEREREREekZPXnuJ7NuP5+krBQA6tbtozguHQjt7fz36oMAxMcn8K//+v1BG6OIiIiIiIicHoXnfuBuPsiqunUABLr9JL+9i2RbaMn2BwfddB3e2/m6667Xkm0REREREZEhQOE5ygzD4Cdv/xzMJgAq/7yR+ek54fZ3DuwjPj6eW2/9Co8/vnSwhikiIiIiIiI9oPAcZe9XfgS5oVfJ22qaqf/bNs7JzgXA3dbK5oZ6kpKSeeSRf8Nq1SvnIiIiIiIiQ4HCcxR1B3y8ufud8PHGF//JQkceZlPoKfSRvZ0bGxsoKXl6UMYoIiIiIiIiPafwHEXv7/+YYELo5+pNBzi4fi9Xjhodbn/3wGdVtr3exoEenoiIiIiIiPSSwnOUNHZ6+du+DwEIBoJsfPETXBmZjE5JBeDTulqqO9rD/e32jEEZp4iIiIiIiPScwnOU/GnX2/iCPgDcf99Fy0HvUU+d3zmwL/xzTk4uixbdP+BjFBERERERkd5ReI6CXd69rPNsBCDZlsSYdifxFgvzD29D1e7389FBNwAmk4n58xdqiyoREREREZEhROWe+yhoBPn9jjfDx9eOv4J5P53FxI4Aqd3dAHx8yE1HIEBOTi7z5y/ksceeGqzhioiIiIiISC8oPPdR6aH1HGgJPVXOSxnBeSPnYDaZuWHSZNq3bgGgs2Ai9xWfy6JF9zNyZN5gDldERERERER6QeG5Dzr8Hby167OtqW6a+AXMJjN+byPtZVsBsGZl8d1H/xuTWSvkRUREREREhioluj54Z+/7tPhaATg79ywmZkwAoHnVKjAMANLmnafgLCIiIiIiMsQp1fWSp62Wjw58AoDNbOX6CVcBYBgGzav+Ee6XNu+8QRmfiIiIiIiIRI/Ccy/9vvItAkYAgAWjLyIrMROArr176D54EIDEiZOIczgGbYwiIiIiIiISHQrPvbDh0Fa21FUAYI9PZ+GYS8JtzaWrwj/rqbOIiIiIiMjwoPDcQ/6gnxc3LA8fXz/hKuItcQAYwSAt69YAYLJaSZk1a1DGKCIiIiIiItGl8NxDHx34JwdbPACMTx/LOY4Z4baO7ZUEmpoASJo6DUtS8qCMUURERERERKJL4bmHPtj3fwCYMHHTxC9gMpnCbS1rSsM/p80pHvCxiYiIiIiISP9QeO6hI4XBFoy5kNFp+eHzht9Py/p1AJji4kiePuO4nxcREREREZGhxzrYAxhqFs+8B39cJ4n+FAIBI3y+rbyMYFsbACkzzsYcHz9YQxQREREREZEo05PnHoqz2MhLcx61XBuOXrKdqiXbIiIiIiIiw4rCcxQEu7tp3bABAHNiIkmuqYM8IhEREREREYkmhecoaNuyCaOrE4CUmbMw22yDPCIRERERERGJJoXnKGhZszr8c+ojamd0AAAODElEQVScuYM4EhEREREREekPCs99FOjooG3zJgAsqakkTSkc5BGJiIiIiIhItCk891Hbxg0YPh8AKbNmY7JYBnlEIiIiIiIiEm0Kz330+SrbaaqyLSIiIiIiMiwpPPdBoLWVtvIyAKwZmSRMKBjkEYmIiIiIiEh/UHjugwPvvweBAACbu7s4eOjgII9IRERERERE+oPCcy/4/X4eeGARa1/6Tfjc/7z9Zy655Dweeug+/H7/4A1OREREREREok7huRfu/v/t3X1MVHe+x/HPwLSAPAhULyA3lVu1jSBSaitWkyp4b/Ufn7rpKrZ66WqkWUNW1KY16YMxtCa1xgi1rdQN1miUK25ssY871hib2mttYkOx2DCXtTpY68qM7CCoMLN/tLJFsGfmdubMwLxfiWk4+db5kHwz5sP5neEPf9Anfzmg3OHJkqRzbrfOXHHJ5XJq3749+tOf/hjihAAAAACAQKI8++n8+fPavXu3CkdlKspikSTZHOf6zNTV1crhOB+KeAAAAACAIKA8+2n9+ufl9Xr1n5n/3nvt8C1F2ev1asOGF82OBgAAAAAIEsqzn2y2T5QxbJgmpN4lSWpuv6K/uf/Rb+7w4U/MjgYAAAAACBLKs586OztVNOpfd51t58/ddg4AAAAAMDRQnv0UFxfX58j2p60DP9s8bNgwsyIBAAAAAIKM8uyn7LQMjfv5U7ZPO9vUevXqgHNFRf9lZiwAAAAAQBBRnv1w9uzfNMFq7f36r46Bj2xbLFF68cUNZsUCAAAAAAQZ5dkPTzzxe01Pz5AkebxeHWl1DDg3duw4Zf7iaDcAAAAAYHCjPPvI4Tivs2dbNOznO88nL/2ov3d1DTibn/+AmdEAAAAAAEFmNR6BJG3fvk3Xrl3Tiyf/V1PTMnSgxX7b2dSff40VAAAAAGBooDz7yOVySZIanU41Op23nYuJiVVp6R/NigUAAAAAMAHHtn2UnJzs01xWVhbPOwMAAADAEEN59tGyZaWGMzExsdq9+39MSAMAAAAAMFNAy7PD4dCKFStUUFCgwsJCbdq0SR6PJ5AvERIul0uTJ+cZzi1Y8DuNHp0V/EAAAAAAAFMF9JnnsrIy5eTkyGaz6fLlyyotLdWIESP01FNPBfJlTDd+/H/I6/X+6kxMTKzWrHnWpEQAAAAAADMF7M5zQ0ODmpqatHbtWiUmJiorK0slJSWqra0N1EuExJ4976inp8dw7tq1Lv35z9UmJAIAAAAAmC1gd54bGxuVmZmp4cOH917LyclRS0uL3G63EhISDP+OqCiLoqIsgYoUEOvWPePzbHu7S1Yrj5EjtKKjo/r8FwhH7CnCHTuKcMeOItwNxR0NWHl2uVxKSkrqc+1mkXY6nT6V59TUeFks4VWeu7u7fZ5NT/83paTEBzEN4LukpLhQRwAMsacId+wowh07inA3lHY0oM88Gz0XbKStrSPs7jxbrVafC3RJyQo5nR1BTgT8uujoKCUlxam9vVM9PYP/A/swNLGnCHfsKMIdO4pwN5h21NcboAErz6mpqXK5XH2uuVwuWSwWpaam+vR3eDxeeTy/rYAH2saNm1ReXmY4N2nSQ0pPH6Xu7vBeDESOnh4P+4iwx54i3LGjCHfsKMLdUNrRgB1AnzBhgi5cuKC2trbeaw0NDRo7dqzi4wfvUeYnnvhvWa2//jMGi8Wi+vqPTUoEAAAAADBbwMpzdna2cnNztXnzZrndbtntdtXU1Ki4uDhQLxEyp0//320LdHR0tM6cOWtYsAEAAAAAg1dAP/qssrJSP/74o6ZNm6alS5dq/vz5Wrx4cSBfIiSSk5PV2tqmLVuqFBsbK6vVqtjYWG3d+oYuXHAqOTk51BEBAAAAAEFk8f7WT/kKoEuX/hHqCIas1iilpMTL6ewYMmf3MbSwoxgM2FOEO3YU4Y4dRbgbTDs6cmSiT3ND55duAQAAAAAQJJRnAAAAAAAMUJ4BAAAAADBAeQYAAAAAwADlGQAAAAAAA5RnAAAAAAAMUJ4BAAAAADBAeQYAAAAAwADlGQAAAAAAA5RnAAAAAAAMUJ4BAAAAADBAeQYAAAAAwADlGQAAAAAAA5RnAAAAAAAMWLxerzfUIQAAAAAACGfceQYAAAAAwADlGQAAAAAAA5RnAAAAAAAMUJ4BAAAAADBAeQYAAAAAwADlGQAAAAAAA5RnAAAAAAAMUJ4BAAAAADBAeQYAAAAAwADlGQAAAAAAA5TnATgcDq1YsUIFBQUqLCzUpk2b5PF4BpzdtWuXZs2apQceeEDFxcX65ptvTE6LSOTPju7du1ezZs1Sfn6+5s2bJ5vNZnJaRCJ/dvSmixcvKj8/X1VVVSalRKTzZ0/tdruWLFmivLw8TZ8+XTt37jQ3LCKSrzvq8XhUWVmpoqIi5efna86cOfrggw9CkBiR5tixY5o6darKy8t/dc7j8WjLli2aOXOmHnroIS1btkznzp0zKWXgUJ4HUFZWprS0NNlsNtXU1Mhms+mdd97pN/fpp5+qqqpKr776qj7//HMVFhbq6aef1tWrV0OQGpHE1x39+OOPtXnzZr3yyis6ceKEnnzySa1atWpQvllhcPF1R3+poqJC0dHRJiUEfN/Trq4uLV++XNOnT9cXX3yhqqoq1dXVyW63hyA1IomvO7p3717t379fO3bs0MmTJ7V69Wo988wzampqCkFqRIq3335bFRUVGj16tOHsnj17VF9fr+rqah05ckRZWVlauXKlvF6vCUkDh/J8i4aGBjU1NWnt2rVKTExUVlaWSkpKVFtb22+2trZWjz32mPLy8hQbG6vly5dLko4cOWJ2bEQQf3a0q6tLq1ev1qRJk3THHXfo8ccfV3x8vE6dOhWC5IgU/uzoTUePHlVzc7NmzJhhXlBENH/29MMPP1RCQoKWL1+uuLg4TZw4UYcOHdKYMWNCkByRwp8dbWxs1KRJk3TPPfcoOjpahYWFSk5O1pkzZ0KQHJEiJiZGdXV1PpXn2tpalZSUaMyYMUpISFB5ebnsdru+/vprE5IGDuX5Fo2NjcrMzNTw4cN7r+Xk5KilpUVut7vfbHZ2du/XUVFRGj9+vBoaGkzLi8jjz47OmzdPixcv7v26vb1dHR0dSktLMy0vIo8/Oyr99EOeDRs26KWXXpLVajUzKiKYP3v61Vdf6d5779W6dev04IMPavbs2XrvvffMjowI48+OzpgxQydOnNC3336r69ev6/Dhw+rs7NTkyZPNjo0IsnTpUiUmJhrOdXV1qbm5uU9vSkhI0OjRowddb6I838LlcikpKanPtZtvWk6ns9/sL9/Qbs7eOgcEkj87+kter1fPP/+88vLy+McUQeXvjm7btk3333+/pkyZYko+QPJvT3/44QcdPnxYU6dO1bFjx1RaWqpnn31Wp0+fNi0vIo8/O/roo49q4cKFmj9/vnJzc7VmzRpt3LhRGRkZpuUFbufKlSvyer1DojfxI/4B+HP2frCd08fQ4O/e3bhxQ88995yam5u1a9euIKUC/sXXHW1ubtb+/ftVX18f5ERAf77uqdfrVU5OjubMmSNJWrBggfbt26ePPvqoz50UINB83dGDBw/q4MGD2r9/v+677z4dP35ca9asUUZGhiZOnBjklIBvhkJv4s7zLVJTU+Vyufpcc7lcslgsSk1N7XM9JSVlwNlb54BA8mdHpZ+OypSWlqq1tVV79uzRiBEjzIqKCOXrjnq9Xq1fv15lZWUaOXKk2TER4fx5Lx05cmS/o4mZmZm6dOlS0HMicvmzo7t379bChQs1ceJExcTEaMaMGZoyZQqPFyAsJCcnKyoqasB9vuuuu0KU6v+H8nyLCRMm6MKFC2pra+u91tDQoLFjxyo+Pr7fbGNjY+/XPT09On36tPLy8kzLi8jjz456vV6Vl5fLarVq586dSklJMTsuIpCvO9ra2qovv/xSlZWVKigoUEFBgd5//33t2LFDCxYsCEV0RBB/3kvHjBmj7777rs9dE4fDoczMTNPyIvL4s6Mej0c9PT19rl2/ft2UnICRmJgYjRs3rk9vam9v1/fffz/oTkZQnm+RnZ2t3Nxcbd68WW63W3a7XTU1NSouLpYkzZ49WydPnpQkFRcX6+DBgzp16pQ6Ozv15ptv6s477+TTYhFU/uxofX29mpubtXXrVsXExIQyNiKIrzuanp6uo0eP6t133+39U1RUpEWLFqm6ujrE3wWGOn/eS+fOnSun06m33npLXV1dOnTokBobGzV37txQfgsY4vzZ0aKiItXV1ampqUnd3d367LPPdPz4cc2cOTOU3wIi2MWLFzV79uzeX49aXFysXbt2yW63y+1267XXXtP48eOVm5sb4qT+4ZnnAVRWVuqFF17QtGnTlJCQoEWLFvV+YnFLS0vv73F+5JFHtHr1aq1atUqXL19Wbm6uqqurFRsbG8r4iAC+7uiBAwfkcDj6fUDYvHnzVFFRYXpuRA5fdjQ6Olrp6el9/r+4uDglJCRwjBum8PW9NC0tTdu3b9fLL7+sN954Q6NGjdK2bdt09913hzI+IoCvO1paWqru7m6tXLlSbW1tyszMVEVFhR5++OFQxscQd7P4dnd3S5JsNpukn05I3LhxQy0tLb0nIBYtWqRLly5pyZIl6ujoUEFBgV5//fXQBP8NLN6h8OQ2AAAAAABBxLFtAAAAAAAMUJ4BAAAAADBAeQYAAAAAwADlGQAAAAAAA5RnAAAAAAAMUJ4BAAAAADBAeQYAAAAAwADlGQAAAAAAA5RnAAAAAAAMUJ4BAAAAADBAeQYAAAAAwADlGQAAAAAAA/8EHzeRPjuROvoAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4MJaPhEmEPf7"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}